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HER2 reader: ViT-S/16 encoders at every stage, the deployed reader, per-slide predictions and paper data

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LICENSE-data.md ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
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+ # Licence for the data
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+
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+ The data in `data/` (per-slide predictions and the data behind the paper's tables and figures) are licensed under the
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+ **Creative Commons Attribution 4.0 International** licence (CC BY 4.0).
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+
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+ Full text: https://creativecommons.org/licenses/by/4.0/legalcode
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+
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+ Please attribute CloudKites AI Lab and the paper "A small HER2 reader for routine H&E slides: real-world deployment"
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+ (Tran and Dang, 2026). The predictions refer to slides of public cohorts, whose own terms also apply: TCGA (NCI GDC open
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+ access), CPTAC-BRCA (open), Yale-HER2 (TCIA HER2-TUMOR-ROIS, CC BY 4.0).
LICENSE-weights.md ADDED
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+ # Licence for the model weights
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+
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+ The model weights in `encoders/`, `checkpoints/` and `reader/` are licensed under the **Creative Commons
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+ Attribution-NonCommercial 4.0 International** licence (CC BY-NC 4.0).
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+
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+ Full text: https://creativecommons.org/licenses/by-nc/4.0/legalcode
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+
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+ You may share and adapt the weights for non-commercial purposes, with attribution to CloudKites AI Lab and the paper
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+ "A small HER2 reader for routine H&E slides: real-world deployment" (Tran and Dang, 2026). Commercial use needs written
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+ permission from CloudKites.
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+
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+ Research use only: the weights are not a medical device and must not be used for clinical decisions.
NOTICE ADDED
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+ This repository's encoders at stage 2 and later were trained by distillation from H-optimus-0 (Bioptimus), which is
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+ released under the Apache License, Version 2.0: https://www.apache.org/licenses/LICENSE-2.0
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+
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+ H-optimus-0 itself is not redistributed here. Our encoders are new weights (a ViT-S/16, 22M parameters) trained to match
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+ its outputs on TCGA tiles.
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+
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+ Training and evaluation data: The Cancer Genome Atlas (NCI Genomic Data Commons, open access); CPTAC-BRCA (open);
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+ Yale-HER2 (The Cancer Imaging Archive, HER2-TUMOR-ROIS, CC BY 4.0). HEROHE (CC BY-NC-ND 3.0) and BCNB (non-commercial)
9
+ were used for evaluation only, and no per-slide data from them are included.
README.md ADDED
@@ -0,0 +1,122 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-nc-4.0
3
+ library_name: timm
4
+ pipeline_tag: image-feature-extraction
5
+ tags:
6
+ - pathology
7
+ - histopathology
8
+ - her2
9
+ - breast-cancer
10
+ - h-and-e
11
+ - vision-transformer
12
+ - multiple-instance-learning
13
+ - safetensors
14
+ ---
15
+
16
+ # HER2 reader: a small ViT-S/16 encoder and HER2 slide classifier for routine H&E
17
+
18
+ Model weights and output data behind the paper **"A small HER2 reader for routine H&E slides: real-world deployment"**
19
+ (Thang Tran, Lan Dang, 2026; arXiv link to follow). We publish them so that anyone can check our numbers, rerun our
20
+ evaluation and build on our encoder.
21
+
22
+ **Research use only.** This is not a medical device and must not be used for clinical decisions. Our reader proposes
23
+ a probability that a breast cancer is HER2-positive from its H&E slide, for a pathologist who reads it beside IHC and
24
+ ISH, never instead of them.
25
+
26
+ ## What is in this repository
27
+
28
+ | Path | What it holds |
29
+ |---|---|
30
+ | `encoders/` | ViT-S/16 tile encoders (22M parameters) at every training stage, with timm parameter names |
31
+ | `checkpoints/` | the same models exactly as trained, in our original layout (including the self-distillation heads), for audit |
32
+ | `reader/her2-jepa2-t2y-s4/` | the deployed reader: encoder, five CLAM-SB fold heads, and a manifest with architecture, tile recipe, operating point and validation |
33
+ | `data/predictions/` | per-slide predictions, by seed: TCGA-BRCA out of fold, Yale-HER2 external, TCGA-BRCA + CPTAC-BRCA under the published protocol |
34
+ | `data/paper/` | data behind the paper's tables and figures |
35
+ | `CHECKSUMS.sha256` | SHA-256 of every file |
36
+
37
+ ### Encoders
38
+
39
+ | File (`encoders/`) | Stage | TCGA-to-Yale AUC* |
40
+ |---|---|---|
41
+ | `stage1_ssl-vits16-final.safetensors` | self-supervised pretraining (DINOv2 + iBOT + KoLeo) on 98.6M TCGA tiles | 0.589 |
42
+ | `stage2_distilled-hoptimus0-step25000.safetensors` | distilled from H-optimus-0 (CLS + 4x4 patch targets), step 25,000 | 0.762 |
43
+ | `stage3a_jepa-round1.safetensors` | one JEPA refinement round | 0.798 |
44
+ | `stage3b_jepa-round2_deployed-encoder.safetensors` | second JEPA round: **the deployed encoder** | **0.812** |
45
+ | `r12a_distilled-1um-step25000.safetensors` | stage 3b distilled again at 1.0 um/px (not adopted) | 0.813** |
46
+ | `r12b_distilled-1um-jepa6000.safetensors` | r12a plus one JEPA round (not adopted) | 0.812** |
47
+
48
+ \* CLAM-SB reader trained on 490 TCGA-BRCA slides, tested on 192 Yale-HER2 slides, mean of 10 seeds (our protocol).
49
+ \*\* Under the published reader's protocol (TCGA + CPTAC training, all tiles, 40 attention-MIL models); the deployed
50
+ encoder scores 0.809 there.
51
+
52
+ ## Load an encoder (timm)
53
+
54
+ ```python
55
+ import timm
56
+ from safetensors.torch import load_file
57
+
58
+ enc = timm.models.vision_transformer.VisionTransformer(
59
+ img_size=224, patch_size=16, embed_dim=384, depth=12, num_heads=6, mlp_ratio=4,
60
+ qkv_bias=True, init_values=1.0, class_token=True, no_embed_class=False, reg_tokens=0,
61
+ global_pool="token", fc_norm=False, num_classes=0)
62
+ enc.load_state_dict(load_file("encoders/stage3b_jepa-round2_deployed-encoder.safetensors"), strict=True)
63
+ enc.eval()
64
+ # input: float32 [N, 3, 224, 224], RGB, ImageNet mean (0.485, 0.456, 0.406) and std (0.229, 0.224, 0.225)
65
+ # output: [N, 384], the class token after the final LayerNorm
66
+ ```
67
+
68
+ Tiles for our reader: 128 um squares read at 0.5 um/px (the coarsest pyramid level at or below 0.5 um/px), resized to
69
+ 224 px by nearest neighbour, tissue only; up to 400 tiles per slide, taken at an even stride across the section. The
70
+ manifest in `reader/` gives every step.
71
+
72
+ ## The deployed reader
73
+
74
+ Five CLAM-SB heads (5-fold cross-validation on 490 TCGA-BRCA slides, seed 4) read one bag of 400 tile vectors. The
75
+ reader's probability is the mean of the five heads' softmax probabilities; at or above **0.27228** it proposes
76
+ "positive". That threshold comes from TCGA-BRCA's out-of-fold predictions, and a laboratory should refit it on its own
77
+ slides, because scores shift between hospitals.
78
+
79
+ | Test set (never trained on) | AUC |
80
+ |---|---|
81
+ | Yale-HER2, 192 slides (5-model ensemble, seed 4) | 0.815 [0.753, 0.876] |
82
+ | BCNB, 1,058 core biopsies (mean of 10 seeds) | 0.628 |
83
+ | HEROHE test split, 150 slides (mean of 10 seeds) | 0.746 |
84
+ | HEROHE IHC 2+ cases, 85 slides (amplified vs not) | 0.761 |
85
+
86
+ At its threshold on Yale-HER2: sensitivity 0.72, specificity 0.79. On a 12-core CPU server it reads a slide in
87
+ 5.2 to 5.6 s.
88
+
89
+ ## Limitations
90
+
91
+ - Its 490 TCGA-BRCA training slides were size-biased: negatives carry less tissue than positives. This inflates the
92
+ Yale AUC by about 0.04; on representative training sets our readers reach about 0.81.
93
+ - Probabilities run low at hospitals other than TCGA's; set the threshold per laboratory.
94
+ - On equivocal IHC 2+ cases (AUC 0.76 on HEROHE) it can help order and prioritise ISH. It does not replace ISH.
95
+ - The best published reader (H-optimus-0, 1.1B parameters, Yale AUC 0.907) remains well ahead. The gap lies in the
96
+ encoder.
97
+
98
+ ## Training data and attributions
99
+
100
+ - **Encoder:** TCGA diagnostic slides (NCI Genomic Data Commons, open access). Distillation teacher: H-optimus-0
101
+ (Bioptimus), Apache-2.0. See `NOTICE`.
102
+ - **Reader heads:** 490 TCGA-BRCA slides with HER2 status from GDC clinical data.
103
+ - **Evaluation cohorts:** Yale-HER2 (TCIA HER2-TUMOR-ROIS, CC BY 4.0), CPTAC-BRCA (open), HEROHE (CC BY-NC-ND 3.0,
104
+ evaluation only) and BCNB (non-commercial, evaluation only). Per-slide data for HEROHE and BCNB are not published
105
+ here; only aggregate numbers appear in the paper.
106
+
107
+ ## Licences
108
+
109
+ - Model weights (`encoders/`, `checkpoints/`, `reader/`): **CC BY-NC 4.0** (`LICENSE-weights.md`).
110
+ - Data (`data/`): **CC BY 4.0** (`LICENSE-data.md`).
111
+ - The distillation teacher's Apache-2.0 notice: `NOTICE`.
112
+
113
+ ## Citation
114
+
115
+ ```bibtex
116
+ @misc{tran2026her2reader,
117
+ title = {A small HER2 reader for routine H\&E slides: real-world deployment},
118
+ author = {Tran, Thang and Dang, Lan},
119
+ year = {2026},
120
+ note = {Model weights and data: https://huggingface.co/cloudkites/her2-reader}
121
+ }
122
+ ```
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1
+ # Data
2
+
3
+ ## predictions/
4
+
5
+ One folder per reader, then per training direction and seed:
6
+
7
+ - `deployed-protocol_clam-sb_recipe-A/` — the deployed reader's protocol: CLAM-SB on 400 tiles at 0.5 um/px, our
8
+ deployed encoder. `t2y`: trained on TCGA-BRCA (490 slides), external test Yale-HER2 (192). `y2t`: trained on
9
+ Yale-HER2, external test TCGA-BRCA. Seeds 1-10; the deployed reader is `t2y/seed4`.
10
+ - `r11o_published-protocol/` — the published reader's protocol with our deployed encoder: attention MIL with non-gated
11
+ attention on every tissue tile at 1.0 um/px, trained on TCGA-BRCA (917) + CPTAC-BRCA (382), external test Yale-HER2.
12
+ Seeds 1-8 (40 models).
13
+ - `r12a_published-protocol/`, `r12b_published-protocol/` — the same protocol with the R12 encoders.
14
+
15
+ Files in each seed folder:
16
+
17
+ - `predictions.csv` — training cohort, 5-fold cross-validation: `fold, split (train/val/test), slide_id, case_id,
18
+ label, score`. Rows with `split == test` are the out-of-fold predictions.
19
+ - `external_predictions.csv` — every fold model's score on every external slide: `fold, split (external), slide_id,
20
+ case_id, label, score`. The seed's reader is the mean over its five folds.
21
+ - `results.csv` — per-fold, pooled and external-ensemble metrics (AUC with DeLong and bootstrap intervals, threshold,
22
+ sensitivity, specificity, PPV, NPV).
23
+ - `folds.csv` — which fold each slide's case was dealt into (case-stratified, fold seed 1337).
24
+
25
+ `label` is HER2 status (1 positive, 0 negative): for TCGA-BRCA from GDC clinical data, for CPTAC-BRCA from its
26
+ proteogenomic ERBB2 status, for Yale-HER2 from the collection's case labels. `score` is the probability of HER2-positive.
27
+
28
+ ## paper/
29
+
30
+ `paper-data/` holds the data files our paper's build reads (tables, figure data, macros); `book-data/` holds the
31
+ files it reads from our technical report's data folder.
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+ x cell s16s50 s16s50_sd d13 d13_sd d14 d14_sd midnight midnight_sd hoptcard hoptcard_sd
2
+ 1 yy 0.7808 0.0174 0.7714 0.0195 0.8064 0.0183 0.8064 0.0091 0.8868 0.0072
3
+ 2 tt 0.6085 0.0042 0.5899 0.0170 0.6688 0.0101 0.5970 0.0028 0.6755 0.0162
4
+ 3 ty 0.5499 0.0167 0.7010 0.0206 0.7157 0.0151 0.7163 0.0086 0.8100 0.0116
5
+ 4 yt 0.5281 0.0060 0.5454 0.0081 0.5733 0.0040 0.6240 0.0039 0.6531 0.0078
data/paper/book-data/her2_dot.dat ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y key group yy yy_sd yy_lo yy_hi tt tt_sd tt_lo tt_hi ty ty_sd ty_lo ty_hi yt yt_sd yt_lo yt_hi
2
+ 2 vits16-random-init ctl 0.5900 0.0040 0.5873 0.5947 0.5080 0.0124 0.4989 0.5221 0.4375 0.0317 0.4041 0.4673 0.4849 0.0020 0.4835 0.4873
3
+ 3 dinov2-vits14 ctl 0.7192 0.0203 0.6988 0.7394 0.5011 0.0226 0.4878 0.5272 0.5889 0.0203 0.5659 0.6044 0.5764 0.0115 0.5631 0.5834
4
+ 4 resnet50-imagenet ctl 0.7009 0.0427 0.6559 0.7408 0.5517 0.0279 0.5315 0.5835 0.6296 0.0149 0.6124 0.6388 0.5606 0.0069 0.5539 0.5677
5
+ 6.6 ssl-vits16-step5k s16 0.7264 0.0064 0.7191 0.7310 0.5697 0.0129 0.5549 0.5778 0.6764 0.0184 0.6556 0.6903 0.5228 0.0041 0.5187 0.5269
6
+ 7.6 ssl-vits16-step20k s16 0.7382 0.0126 0.7285 0.7525 0.5675 0.0106 0.5602 0.5797 0.6174 0.0430 0.5685 0.6490 0.5451 0.0010 0.5444 0.5463
7
+ 8.6 ssl-vits16-step35k s16 0.8039 0.0106 0.7919 0.8120 0.5992 0.0082 0.5898 0.6047 0.5613 0.0149 0.5464 0.5763 0.5306 0.0038 0.5262 0.5333
8
+ 9.6 ssl-vits16-step40k s16 0.7919 0.0193 0.7696 0.8035 0.6199 0.0090 0.6102 0.6278 0.5651 0.0174 0.5469 0.5814 0.5144 0.0034 0.5107 0.5173
9
+ 10.6 ssl-vits16-step45k s16 0.7601 0.0245 0.7400 0.7873 0.5887 0.0192 0.5666 0.6017 0.5873 0.0660 0.5455 0.6633 0.5253 0.0061 0.5190 0.5312
10
+ 11.6 ssl-vits16-step50k s16 0.7808 0.0174 0.7611 0.7939 0.6085 0.0042 0.6036 0.6110 0.5499 0.0167 0.5307 0.5603 0.5281 0.0060 0.5233 0.5348
11
+ 12.6 ssl-vits16-step55k s16 0.7880 0.0285 0.7561 0.8109 0.5888 0.0031 0.5854 0.5915 0.6004 0.0520 0.5576 0.6583 0.5322 0.0064 0.5260 0.5387
12
+ 13.6 ssl-vits16-step60k s16 0.7775 0.0090 0.7681 0.7860 0.5958 0.0062 0.5887 0.5999 0.5922 0.0314 0.5560 0.6112 0.5318 0.0034 0.5296 0.5358
13
+ 14.6 ssl-vits16-step65k s16 0.7588 0.0154 0.7486 0.7765 0.6211 0.0165 0.6104 0.6402 0.5530 0.0541 0.4957 0.6031 0.5177 0.0018 0.5157 0.5192
14
+ 15.6 ssl-vits16-final s16 0.7675 0.0267 0.7376 0.7892 0.5891 0.0128 0.5754 0.6009 0.5841 0.0385 0.5417 0.6167 0.5205 0.0029 0.5182 0.5238
15
+ 18.2 ssl-vitb16-step10k b16 0.7575 0.0358 0.7255 0.7961 0.5877 0.0045 0.5839 0.5927 0.5724 0.0202 0.5527 0.5930 0.5307 0.0105 0.5201 0.5411
16
+ 19.2 ssl-vitb16-step35k b16 0.8290 0.0099 0.8217 0.8403 0.5819 0.0184 0.5690 0.6030 0.6380 0.0233 0.6212 0.6646 0.5455 0.0017 0.5444 0.5474
17
+ 20.2 ssl-vitb16-step40k b16 0.7934 0.0135 0.7781 0.8035 0.6074 0.0161 0.5909 0.6231 0.6651 0.0377 0.6307 0.7053 0.5472 0.0057 0.5427 0.5536
18
+ 22.8 distill-midnight-20k dst 0.7714 0.0195 0.7494 0.7869 0.5899 0.0170 0.5704 0.6005 0.7010 0.0206 0.6799 0.7211 0.5454 0.0081 0.5373 0.5535
19
+ 23.8 distill-hoptimus-20k dst 0.8064 0.0183 0.7861 0.8215 0.6688 0.0101 0.6591 0.6793 0.7157 0.0151 0.7056 0.7330 0.5733 0.0040 0.5704 0.5778
20
+ 24.8 distill-midnight-5k-from-random dst 0.7616 0.0241 0.7352 0.7823 0.5474 0.0242 0.5200 0.5659 0.6205 0.0347 0.5811 0.6464 0.5288 0.0026 0.5260 0.5311
21
+ 25.8 distill-midnight-5k-from-vits16-step50k dst 0.7718 0.0161 0.7532 0.7811 0.5688 0.0093 0.5582 0.5761 0.7244 0.0175 0.7071 0.7422 0.5576 0.0113 0.5448 0.5659
22
+ 26.8 distill-midnight-5k-from-vits16-final dst 0.7923 0.0214 0.7697 0.8122 0.5878 0.0072 0.5804 0.5949 0.6512 0.0293 0.6178 0.6725 0.5526 0.0017 0.5516 0.5546
23
+ 27.8 distill-hoptimus-5k-from-random dst 0.7922 0.0088 0.7849 0.8019 0.5922 0.0143 0.5810 0.6083 0.7387 0.0281 0.7071 0.7607 0.5632 0.0016 0.5618 0.5649
24
+ 28.8 distill-hoptimus-5k-from-vits16-step50k dst 0.8143 0.0083 0.8089 0.8238 0.6361 0.0038 0.6322 0.6398 0.7393 0.0173 0.7215 0.7562 0.6215 0.0038 0.6186 0.6258
25
+ 29.8 distill-hoptimus-5k-from-vits16-final dst 0.8196 0.0197 0.7974 0.8350 0.6228 0.0229 0.5982 0.6435 0.7443 0.0219 0.7197 0.7616 0.5930 0.0059 0.5864 0.5976
26
+ 32.4 distill-hoptimus-vitb16-5k-from-vitb16-step40k dstb 0.8177 0.0098 0.8110 0.8290 0.6332 0.0157 0.6211 0.6509 0.7757 0.0098 0.7644 0.7826 0.6406 0.0080 0.6328 0.6488
27
+ 33.4 distill-hoptimus-vitb16-5k-from-vitb16-step45k dstb 0.7765 0.0094 0.7681 0.7867 0.6329 0.0143 0.6170 0.6444 0.7623 0.0040 0.7578 0.7654 0.6215 0.0069 0.6153 0.6289
28
+ 34.4 distill-hoptimus-vitb16-5k-from-vitb16-step50k dstb 0.8032 0.0397 0.7664 0.8453 0.6148 0.0022 0.6130 0.6173 0.7547 0.0075 0.7470 0.7619 0.6136 0.0012 0.6127 0.6149
29
+ 37 hibou-b ref 0.7794 0.0119 0.7684 0.7920 0.6442 0.0161 0.6262 0.6569 0.7172 0.0299 0.6932 0.7506 0.6309 0.0105 0.6187 0.6374
30
+ 38 phikon ref 0.8756 0.0047 0.8706 0.8800 0.6690 0.0085 0.6613 0.6780 0.8128 0.0191 0.7914 0.8278 0.6606 0.0003 0.6602 0.6609
31
+ 39 virchow2 ref 0.8673 0.0086 0.8576 0.8742 0.6336 0.0146 0.6247 0.6505 0.7425 0.0349 0.7089 0.7785 0.6541 0.0058 0.6494 0.6605
32
+ 40 midnight12k ref 0.8064 0.0091 0.7960 0.8129 0.5970 0.0028 0.5944 0.6001 0.7163 0.0086 0.7107 0.7262 0.6240 0.0039 0.6195 0.6267
33
+ 41 midnight12k-cls-mean ref 0.8114 0.0112 0.7993 0.8213 0.6105 0.0084 0.6016 0.6184 0.7337 0.0209 0.7170 0.7571 0.6376 0.0039 0.6334 0.6411
34
+ 42 midnight12k-1.0um ref 0.8013 0.0060 0.7953 0.8073 0.5858 0.0127 0.5723 0.5976 0.7243 0.0269 0.6932 0.7400 0.6087 0.0054 0.6054 0.6150
35
+ 43 hoptimus0-imagenetnorm ref 0.8978 0.0104 0.8862 0.9063 0.6685 0.0232 0.6442 0.6905 0.7977 0.0172 0.7786 0.8121 0.6562 0.0013 0.6549 0.6575
36
+ 44 hoptimus0-imagenetnorm-repeat ref 0.8954 0.0143 0.8793 0.9066 0.6683 0.0145 0.6515 0.6771 0.7871 0.0310 0.7534 0.8144 0.6562 0.0052 0.6520 0.6621
37
+ 45 hoptimus0-cardnorm ref 0.8868 0.0072 0.8792 0.8935 0.6755 0.0162 0.6632 0.6938 0.8100 0.0116 0.7986 0.8218 0.6531 0.0078 0.6445 0.6596
38
+ 46 hoptimus0-cls-mean ref 0.8925 0.0157 0.8747 0.9043 0.6723 0.0179 0.6553 0.6909 0.8028 0.0253 0.7736 0.8194 0.6630 0.0057 0.6566 0.6674
39
+ 47 hoptimus0-1.0um ref 0.9088 0.0066 0.9038 0.9163 0.6591 0.0153 0.6415 0.6696 0.8033 0.0109 0.7925 0.8143 0.6419 0.0071 0.6348 0.6491
data/paper/book-data/her2_dot_rows.dat ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y label
2
+ 1 \textbf{Controls}
3
+ 2 random weights, ViT-S/16
4
+ 3 DINOv2 ViT-S/14 (natural images)
5
+ 4 ResNet-50, ImageNet (Aug.)
6
+ 5.6 \textbf{Ours: ssl-vits16}
7
+ 6.6 ssl-vits16 step 5k
8
+ 7.6 ssl-vits16 step 20k
9
+ 8.6 ssl-vits16 step 35k
10
+ 9.6 ssl-vits16 step 40k
11
+ 10.6 ssl-vits16 step 45k
12
+ 11.6 ssl-vits16 step 50k
13
+ 12.6 ssl-vits16 step 55k
14
+ 13.6 ssl-vits16 step 60k
15
+ 14.6 ssl-vits16 step 65k
16
+ 15.6 ssl-vits16 final (93k)
17
+ 17.2 \textbf{Ours: ssl-vitb16}
18
+ 18.2 ssl-vitb16 step 10k
19
+ 19.2 ssl-vitb16 step 35k
20
+ 20.2 ssl-vitb16 step 40k
21
+ 21.8 \textbf{Ours: distilled students}
22
+ 22.8 D13: Midnight-12k teacher, 20k steps
23
+ 23.8 D14: H-optimus-0 teacher, 20k steps
24
+ 24.8 D15: Midnight, 5k, from random
25
+ 25.8 D15: Midnight, 5k, from step 50k
26
+ 26.8 D15: Midnight, 5k, from final
27
+ 27.8 D16: H-optimus-0, 5k, from random
28
+ 28.8 D16: H-optimus-0, 5k, from step 50k
29
+ 29.8 \textbf{\textcolor{hrBest}{D16: H-optimus-0, 5k, from final}}
30
+ 31.4 \textbf{Ours: ViT-B/16 students}
31
+ 32.4 D18: H-optimus-0, ViT-B/16, 5k, from step 40k
32
+ 33.4 D18: H-optimus-0, ViT-B/16, 5k, from step 45k
33
+ 34.4 D18: H-optimus-0, ViT-B/16, 5k, from step 50k
34
+ 36 \textbf{Released encoders}
35
+ 37 Hibou-B (Aug.)
36
+ 38 Phikon v1, ViT-B/16 (Aug.)
37
+ 39 Virchow2 (Aug.)
38
+ 40 Midnight-12k, CLS
39
+ 41 Midnight-12k, CLS+mean
40
+ 42 Midnight-12k, CLS, 1.0\,\textmu m/px
41
+ 43 H-optimus-0, ImageNet norm. (Aug.)
42
+ 44 H-optimus-0, ImageNet norm. (Sep.)
43
+ 45 H-optimus-0, card norm., CLS
44
+ 46 H-optimus-0, card norm., CLS+mean
45
+ 47 H-optimus-0, card norm., CLS, 1.0\,\textmu m/px
data/paper/book-data/her2_leader.dat ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y key cls params gmacs cpu400 yy yy_sd yy_rank tt tt_sd tt_rank ty ty_sd ty_rank yt yt_sd yt_rank
2
+ 1 phikon ref 8.57979e+07 17.56 22.98 0.8756 0.0047 2 0.6690 0.0085 2 0.8128 0.0191 1 0.6606 0.0003 1
3
+ 2 hoptimus0-cardnorm ref 1.13465e+09 304.17 312.29 0.8868 0.0072 1 0.6755 0.0162 1 0.8100 0.0116 2 0.6531 0.0078 3
4
+ 3 distill-hoptimus-vitb16-5k-from-vitb16-step40k ours 8.57979e+07 17.56 22.98 0.8177 0.0098 5 0.6332 0.0157 5 0.7757 0.0098 3 0.6406 0.0080 4
5
+ 4 distill-hoptimus-5k-from-vits16-final best 2.16653e+07 4.60 8.43 0.8196 0.0197 4 0.6228 0.0229 6 0.7443 0.0219 4 0.5930 0.0059 7
6
+ 5 virchow2 ref 6.31151e+08 170.07 nan 0.8673 0.0086 3 0.6336 0.0146 4 0.7425 0.0349 5 0.6541 0.0058 2
7
+ 6 midnight12k-cls-mean ref 1.13465e+09 299.39 312.29 0.8114 0.0112 6 0.6105 0.0084 7 0.7337 0.0209 6 0.6376 0.0039 5
8
+ 7 hibou-b ref 8.57211e+07 23.54 nan 0.7794 0.0119 7 0.6442 0.0161 3 0.7172 0.0299 7 0.6309 0.0105 6
9
+ 8 distill-midnight-20k ours 2.16653e+07 4.60 8.43 0.7714 0.0195 8 0.5899 0.0170 8 0.7010 0.0206 8 0.5454 0.0081 10
10
+ 9 resnet50-imagenet ctl 2.56e+07 4.10 nan 0.7009 0.0427 11 0.5517 0.0279 10 0.6296 0.0149 9 0.5606 0.0069 9
11
+ 10 dinov2-vits14 ctl 2.16192e+07 6.12 nan 0.7192 0.0203 10 0.5011 0.0226 11 0.5889 0.0203 10 0.5764 0.0115 8
12
+ 11 ssl-vits16-final ours 2.16653e+07 4.60 8.43 0.7675 0.0267 9 0.5891 0.0128 9 0.5841 0.0385 11 0.5205 0.0029 11
data/paper/book-data/her2_leader_rows.dat ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y label
2
+ 1 Phikon (86M)
3
+ 2 H-optimus-0 (1.1B)
4
+ 3 Ours, D18: ViT-B student of H-optimus-0 (86M)
5
+ 4 \textbf{Ours, D16: student of H-optimus-0} (22M)
6
+ 5 Virchow2 (631M)
7
+ 6 Midnight-12k (1.1B)
8
+ 7 Hibou-B (86M)
9
+ 8 Ours, D13: student of Midnight-12k (22M)
10
+ 9 ResNet-50 (26M)
11
+ 10 DINOv2 ViT-S/14 (22M)
12
+ 11 Ours, ssl-vits16: self-supervised (22M)
data/paper/book-data/her2_macros.tex ADDED
@@ -0,0 +1,2112 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ % written by her2_data.py from data/her2_raw; do not edit
2
+ \herset{updated}{2 October 2026}
3
+ \herset{n-encoders}{38}
4
+ \herset{n-runs}{228}
5
+ \herset{rand-yy}{0.590}
6
+ \herset{rand-yy-sd}{0.004}
7
+ \herset{rand-yy-v}{0.5900}
8
+ \herset{rand-yy-mf}{0.602}
9
+ \herset{rand-yy-mfsd}{0.010}
10
+ \herset{rand-yy-s1}{0.588}
11
+ \herset{rand-yy-s2}{0.587}
12
+ \herset{rand-yy-s3}{0.595}
13
+ \herset{rand-tt}{0.508}
14
+ \herset{rand-tt-sd}{0.012}
15
+ \herset{rand-tt-v}{0.5080}
16
+ \herset{rand-tt-mf}{0.517}
17
+ \herset{rand-tt-mfsd}{0.014}
18
+ \herset{rand-tt-s1}{0.503}
19
+ \herset{rand-tt-s2}{0.522}
20
+ \herset{rand-tt-s3}{0.499}
21
+ \herset{rand-ty}{0.438}
22
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375
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376
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377
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378
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379
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380
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381
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382
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383
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384
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385
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386
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387
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388
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389
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390
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391
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392
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393
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394
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395
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396
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397
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398
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399
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400
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401
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402
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403
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404
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405
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406
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407
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408
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409
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410
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411
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412
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413
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414
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415
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416
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417
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418
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419
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420
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421
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422
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423
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424
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425
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427
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428
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429
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430
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431
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432
+ \herset{s16final-probe}{0.342}
433
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434
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435
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436
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437
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438
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439
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440
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441
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442
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443
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444
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445
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446
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447
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448
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449
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450
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451
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452
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453
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454
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455
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456
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457
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458
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459
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460
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461
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462
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463
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464
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465
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466
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467
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468
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469
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470
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471
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472
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473
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474
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475
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476
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477
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478
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479
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480
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481
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482
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483
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484
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485
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486
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487
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488
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489
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490
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491
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492
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493
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494
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495
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496
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497
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498
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499
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500
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501
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502
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503
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504
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505
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506
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507
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508
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509
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510
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511
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512
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513
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514
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515
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516
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517
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518
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519
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520
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521
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522
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523
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524
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525
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526
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527
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528
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529
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530
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531
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532
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533
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534
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535
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536
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537
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538
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539
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540
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541
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542
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543
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544
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545
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546
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547
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548
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549
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550
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551
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552
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553
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554
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555
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556
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557
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558
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559
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560
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561
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562
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563
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564
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565
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566
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567
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568
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569
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570
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571
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572
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573
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574
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575
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576
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577
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578
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579
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580
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581
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582
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583
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585
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586
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587
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588
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589
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590
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591
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592
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593
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594
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595
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596
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597
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598
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599
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600
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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634
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635
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636
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637
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638
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639
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640
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641
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642
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643
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
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665
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666
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667
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668
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669
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670
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671
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672
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673
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674
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675
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676
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677
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678
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679
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
+ \herset{d16rand-yt-s2}{0.563}
728
+ \herset{d16rand-yt-s3}{0.562}
729
+ \herset{d16rand-probe}{0.329}
730
+ \herset{d16s50k-yy}{0.814}
731
+ \herset{d16s50k-yy-sd}{0.008}
732
+ \herset{d16s50k-yy-v}{0.8143}
733
+ \herset{d16s50k-yy-mf}{0.829}
734
+ \herset{d16s50k-yy-mfsd}{0.004}
735
+ \herset{d16s50k-yy-s1}{0.809}
736
+ \herset{d16s50k-yy-s2}{0.810}
737
+ \herset{d16s50k-yy-s3}{0.824}
738
+ \herset{d16s50k-tt}{0.636}
739
+ \herset{d16s50k-tt-sd}{0.004}
740
+ \herset{d16s50k-tt-v}{0.6361}
741
+ \herset{d16s50k-tt-mf}{0.672}
742
+ \herset{d16s50k-tt-mfsd}{0.008}
743
+ \herset{d16s50k-tt-s1}{0.640}
744
+ \herset{d16s50k-tt-s2}{0.632}
745
+ \herset{d16s50k-tt-s3}{0.636}
746
+ \herset{d16s50k-ty}{0.739}
747
+ \herset{d16s50k-ty-sd}{0.017}
748
+ \herset{d16s50k-ty-v}{0.7393}
749
+ \herset{d16s50k-ty-mf}{0.722}
750
+ \herset{d16s50k-ty-mfsd}{0.013}
751
+ \herset{d16s50k-ty-s1}{0.756}
752
+ \herset{d16s50k-ty-s2}{0.740}
753
+ \herset{d16s50k-ty-s3}{0.722}
754
+ \herset{d16s50k-yt}{0.622}
755
+ \herset{d16s50k-yt-sd}{0.004}
756
+ \herset{d16s50k-yt-v}{0.6215}
757
+ \herset{d16s50k-yt-mf}{0.596}
758
+ \herset{d16s50k-yt-mfsd}{0.006}
759
+ \herset{d16s50k-yt-s1}{0.620}
760
+ \herset{d16s50k-yt-s2}{0.619}
761
+ \herset{d16s50k-yt-s3}{0.626}
762
+ \herset{d16s50k-probe}{0.446}
763
+ \herset{d16final-yy}{0.820}
764
+ \herset{d16final-yy-sd}{0.020}
765
+ \herset{d16final-yy-v}{0.8196}
766
+ \herset{d16final-yy-mf}{0.842}
767
+ \herset{d16final-yy-mfsd}{0.009}
768
+ \herset{d16final-yy-s1}{0.797}
769
+ \herset{d16final-yy-s2}{0.835}
770
+ \herset{d16final-yy-s3}{0.826}
771
+ \herset{d16final-tt}{0.623}
772
+ \herset{d16final-tt-sd}{0.023}
773
+ \herset{d16final-tt-v}{0.6228}
774
+ \herset{d16final-tt-mf}{0.658}
775
+ \herset{d16final-tt-mfsd}{0.016}
776
+ \herset{d16final-tt-s1}{0.598}
777
+ \herset{d16final-tt-s2}{0.644}
778
+ \herset{d16final-tt-s3}{0.627}
779
+ \herset{d16final-ty}{0.744}
780
+ \herset{d16final-ty-sd}{0.022}
781
+ \herset{d16final-ty-v}{0.7443}
782
+ \herset{d16final-ty-mf}{0.728}
783
+ \herset{d16final-ty-mfsd}{0.013}
784
+ \herset{d16final-ty-s1}{0.762}
785
+ \herset{d16final-ty-s2}{0.751}
786
+ \herset{d16final-ty-s3}{0.720}
787
+ \herset{d16final-yt}{0.593}
788
+ \herset{d16final-yt-sd}{0.006}
789
+ \herset{d16final-yt-v}{0.5930}
790
+ \herset{d16final-yt-mf}{0.577}
791
+ \herset{d16final-yt-mfsd}{0.003}
792
+ \herset{d16final-yt-s1}{0.586}
793
+ \herset{d16final-yt-s2}{0.598}
794
+ \herset{d16final-yt-s3}{0.595}
795
+ \herset{d16final-probe}{0.451}
796
+ \herset{d18s40k-yy}{0.818}
797
+ \herset{d18s40k-yy-sd}{0.010}
798
+ \herset{d18s40k-yy-v}{0.8177}
799
+ \herset{d18s40k-yy-mf}{0.847}
800
+ \herset{d18s40k-yy-mfsd}{0.001}
801
+ \herset{d18s40k-yy-s1}{0.811}
802
+ \herset{d18s40k-yy-s2}{0.813}
803
+ \herset{d18s40k-yy-s3}{0.829}
804
+ \herset{d18s40k-tt}{0.633}
805
+ \herset{d18s40k-tt-sd}{0.016}
806
+ \herset{d18s40k-tt-v}{0.6332}
807
+ \herset{d18s40k-tt-mf}{0.662}
808
+ \herset{d18s40k-tt-mfsd}{0.006}
809
+ \herset{d18s40k-tt-s1}{0.651}
810
+ \herset{d18s40k-tt-s2}{0.627}
811
+ \herset{d18s40k-tt-s3}{0.621}
812
+ \herset{d18s40k-ty}{0.776}
813
+ \herset{d18s40k-ty-sd}{0.010}
814
+ \herset{d18s40k-ty-v}{0.7757}
815
+ \herset{d18s40k-ty-mf}{0.759}
816
+ \herset{d18s40k-ty-mfsd}{0.012}
817
+ \herset{d18s40k-ty-s1}{0.780}
818
+ \herset{d18s40k-ty-s2}{0.783}
819
+ \herset{d18s40k-ty-s3}{0.764}
820
+ \herset{d18s40k-yt}{0.641}
821
+ \herset{d18s40k-yt-sd}{0.008}
822
+ \herset{d18s40k-yt-v}{0.6406}
823
+ \herset{d18s40k-yt-mf}{0.622}
824
+ \herset{d18s40k-yt-mfsd}{0.003}
825
+ \herset{d18s40k-yt-s1}{0.633}
826
+ \herset{d18s40k-yt-s2}{0.649}
827
+ \herset{d18s40k-yt-s3}{0.640}
828
+ \herset{d18s40k-probe}{0.471}
829
+ \herset{d18s45k-yy}{0.777}
830
+ \herset{d18s45k-yy-sd}{0.009}
831
+ \herset{d18s45k-yy-v}{0.7765}
832
+ \herset{d18s45k-yy-mf}{0.829}
833
+ \herset{d18s45k-yy-mfsd}{0.013}
834
+ \herset{d18s45k-yy-s1}{0.775}
835
+ \herset{d18s45k-yy-s2}{0.768}
836
+ \herset{d18s45k-yy-s3}{0.787}
837
+ \herset{d18s45k-tt}{0.633}
838
+ \herset{d18s45k-tt-sd}{0.014}
839
+ \herset{d18s45k-tt-v}{0.6329}
840
+ \herset{d18s45k-tt-mf}{0.668}
841
+ \herset{d18s45k-tt-mfsd}{0.014}
842
+ \herset{d18s45k-tt-s1}{0.637}
843
+ \herset{d18s45k-tt-s2}{0.617}
844
+ \herset{d18s45k-tt-s3}{0.644}
845
+ \herset{d18s45k-ty}{0.762}
846
+ \herset{d18s45k-ty-sd}{0.004}
847
+ \herset{d18s45k-ty-v}{0.7623}
848
+ \herset{d18s45k-ty-mf}{0.747}
849
+ \herset{d18s45k-ty-mfsd}{0.009}
850
+ \herset{d18s45k-ty-s1}{0.758}
851
+ \herset{d18s45k-ty-s2}{0.764}
852
+ \herset{d18s45k-ty-s3}{0.765}
853
+ \herset{d18s45k-yt}{0.621}
854
+ \herset{d18s45k-yt-sd}{0.007}
855
+ \herset{d18s45k-yt-v}{0.6215}
856
+ \herset{d18s45k-yt-mf}{0.604}
857
+ \herset{d18s45k-yt-mfsd}{0.005}
858
+ \herset{d18s45k-yt-s1}{0.615}
859
+ \herset{d18s45k-yt-s2}{0.620}
860
+ \herset{d18s45k-yt-s3}{0.629}
861
+ \herset{d18s45k-probe}{0.480}
862
+ \herset{d18s50k-yy}{0.803}
863
+ \herset{d18s50k-yy-sd}{0.040}
864
+ \herset{d18s50k-yy-v}{0.8032}
865
+ \herset{d18s50k-yy-mf}{0.841}
866
+ \herset{d18s50k-yy-mfsd}{0.012}
867
+ \herset{d18s50k-yy-s1}{0.766}
868
+ \herset{d18s50k-yy-s2}{0.798}
869
+ \herset{d18s50k-yy-s3}{0.845}
870
+ \herset{d18s50k-tt}{0.615}
871
+ \herset{d18s50k-tt-sd}{0.002}
872
+ \herset{d18s50k-tt-v}{0.6148}
873
+ \herset{d18s50k-tt-mf}{0.641}
874
+ \herset{d18s50k-tt-mfsd}{0.002}
875
+ \herset{d18s50k-tt-s1}{0.617}
876
+ \herset{d18s50k-tt-s2}{0.614}
877
+ \herset{d18s50k-tt-s3}{0.613}
878
+ \herset{d18s50k-ty}{0.755}
879
+ \herset{d18s50k-ty-sd}{0.007}
880
+ \herset{d18s50k-ty-v}{0.7547}
881
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882
+ \herset{d18s50k-ty-mfsd}{0.011}
883
+ \herset{d18s50k-ty-s1}{0.762}
884
+ \herset{d18s50k-ty-s2}{0.755}
885
+ \herset{d18s50k-ty-s3}{0.747}
886
+ \herset{d18s50k-yt}{0.614}
887
+ \herset{d18s50k-yt-sd}{0.001}
888
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889
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890
+ \herset{d18s50k-yt-mfsd}{0.004}
891
+ \herset{d18s50k-yt-s1}{0.613}
892
+ \herset{d18s50k-yt-s2}{0.615}
893
+ \herset{d18s50k-yt-s3}{0.613}
894
+ \herset{d18s50k-probe}{0.490}
895
+ \herset{hibou-yy}{0.779}
896
+ \herset{hibou-yy-sd}{0.012}
897
+ \herset{hibou-yy-v}{0.7794}
898
+ \herset{hibou-yy-mf}{0.817}
899
+ \herset{hibou-yy-mfsd}{0.015}
900
+ \herset{hibou-yy-s1}{0.792}
901
+ \herset{hibou-yy-s2}{0.768}
902
+ \herset{hibou-yy-s3}{0.778}
903
+ \herset{hibou-tt}{0.644}
904
+ \herset{hibou-tt-sd}{0.016}
905
+ \herset{hibou-tt-v}{0.6442}
906
+ \herset{hibou-tt-mf}{0.664}
907
+ \herset{hibou-tt-mfsd}{0.009}
908
+ \herset{hibou-tt-s1}{0.650}
909
+ \herset{hibou-tt-s2}{0.626}
910
+ \herset{hibou-tt-s3}{0.657}
911
+ \herset{hibou-ty}{0.717}
912
+ \herset{hibou-ty-sd}{0.030}
913
+ \herset{hibou-ty-v}{0.7172}
914
+ \herset{hibou-ty-mf}{0.679}
915
+ \herset{hibou-ty-mfsd}{0.024}
916
+ \herset{hibou-ty-s1}{0.693}
917
+ \herset{hibou-ty-s2}{0.708}
918
+ \herset{hibou-ty-s3}{0.751}
919
+ \herset{hibou-yt}{0.631}
920
+ \herset{hibou-yt-sd}{0.011}
921
+ \herset{hibou-yt-v}{0.6309}
922
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923
+ \herset{hibou-yt-mfsd}{0.005}
924
+ \herset{hibou-yt-s1}{0.637}
925
+ \herset{hibou-yt-s2}{0.619}
926
+ \herset{hibou-yt-s3}{0.637}
927
+ \herset{phikon-yy}{0.876}
928
+ \herset{phikon-yy-sd}{0.005}
929
+ \herset{phikon-yy-v}{0.8756}
930
+ \herset{phikon-yy-mf}{0.890}
931
+ \herset{phikon-yy-mfsd}{0.006}
932
+ \herset{phikon-yy-s1}{0.876}
933
+ \herset{phikon-yy-s2}{0.880}
934
+ \herset{phikon-yy-s3}{0.871}
935
+ \herset{phikon-tt}{0.669}
936
+ \herset{phikon-tt-sd}{0.008}
937
+ \herset{phikon-tt-v}{0.6690}
938
+ \herset{phikon-tt-mf}{0.687}
939
+ \herset{phikon-tt-mfsd}{0.006}
940
+ \herset{phikon-tt-s1}{0.661}
941
+ \herset{phikon-tt-s2}{0.668}
942
+ \herset{phikon-tt-s3}{0.678}
943
+ \herset{phikon-ty}{0.813}
944
+ \herset{phikon-ty-sd}{0.019}
945
+ \herset{phikon-ty-v}{0.8128}
946
+ \herset{phikon-ty-mf}{0.768}
947
+ \herset{phikon-ty-mfsd}{0.017}
948
+ \herset{phikon-ty-s1}{0.791}
949
+ \herset{phikon-ty-s2}{0.828}
950
+ \herset{phikon-ty-s3}{0.819}
951
+ \herset{phikon-yt}{0.661}
952
+ \herset{phikon-yt-sd}{0.000}
953
+ \herset{phikon-yt-v}{0.6606}
954
+ \herset{phikon-yt-mf}{0.648}
955
+ \herset{phikon-yt-mfsd}{0.003}
956
+ \herset{phikon-yt-s1}{0.661}
957
+ \herset{phikon-yt-s2}{0.661}
958
+ \herset{phikon-yt-s3}{0.660}
959
+ \herset{phikon-probe}{0.551}
960
+ \herset{virchow2-yy}{0.867}
961
+ \herset{virchow2-yy-sd}{0.009}
962
+ \herset{virchow2-yy-v}{0.8673}
963
+ \herset{virchow2-yy-mf}{0.889}
964
+ \herset{virchow2-yy-mfsd}{0.010}
965
+ \herset{virchow2-yy-s1}{0.874}
966
+ \herset{virchow2-yy-s2}{0.870}
967
+ \herset{virchow2-yy-s3}{0.858}
968
+ \herset{virchow2-tt}{0.634}
969
+ \herset{virchow2-tt-sd}{0.015}
970
+ \herset{virchow2-tt-v}{0.6336}
971
+ \herset{virchow2-tt-mf}{0.665}
972
+ \herset{virchow2-tt-mfsd}{0.019}
973
+ \herset{virchow2-tt-s1}{0.626}
974
+ \herset{virchow2-tt-s2}{0.625}
975
+ \herset{virchow2-tt-s3}{0.650}
976
+ \herset{virchow2-ty}{0.743}
977
+ \herset{virchow2-ty-sd}{0.035}
978
+ \herset{virchow2-ty-v}{0.7425}
979
+ \herset{virchow2-ty-mf}{0.708}
980
+ \herset{virchow2-ty-mfsd}{0.024}
981
+ \herset{virchow2-ty-s1}{0.740}
982
+ \herset{virchow2-ty-s2}{0.709}
983
+ \herset{virchow2-ty-s3}{0.779}
984
+ \herset{virchow2-yt}{0.654}
985
+ \herset{virchow2-yt-sd}{0.006}
986
+ \herset{virchow2-yt-v}{0.6541}
987
+ \herset{virchow2-yt-mf}{0.636}
988
+ \herset{virchow2-yt-mfsd}{0.009}
989
+ \herset{virchow2-yt-s1}{0.652}
990
+ \herset{virchow2-yt-s2}{0.649}
991
+ \herset{virchow2-yt-s3}{0.661}
992
+ \herset{midnight-yy}{0.806}
993
+ \herset{midnight-yy-sd}{0.009}
994
+ \herset{midnight-yy-v}{0.8064}
995
+ \herset{midnight-yy-mf}{0.834}
996
+ \herset{midnight-yy-mfsd}{0.003}
997
+ \herset{midnight-yy-s1}{0.813}
998
+ \herset{midnight-yy-s2}{0.810}
999
+ \herset{midnight-yy-s3}{0.796}
1000
+ \herset{midnight-tt}{0.597}
1001
+ \herset{midnight-tt-sd}{0.003}
1002
+ \herset{midnight-tt-v}{0.5970}
1003
+ \herset{midnight-tt-mf}{0.611}
1004
+ \herset{midnight-tt-mfsd}{0.005}
1005
+ \herset{midnight-tt-s1}{0.597}
1006
+ \herset{midnight-tt-s2}{0.600}
1007
+ \herset{midnight-tt-s3}{0.594}
1008
+ \herset{midnight-ty}{0.716}
1009
+ \herset{midnight-ty-sd}{0.009}
1010
+ \herset{midnight-ty-v}{0.7163}
1011
+ \herset{midnight-ty-mf}{0.695}
1012
+ \herset{midnight-ty-mfsd}{0.003}
1013
+ \herset{midnight-ty-s1}{0.712}
1014
+ \herset{midnight-ty-s2}{0.711}
1015
+ \herset{midnight-ty-s3}{0.726}
1016
+ \herset{midnight-yt}{0.624}
1017
+ \herset{midnight-yt-sd}{0.004}
1018
+ \herset{midnight-yt-v}{0.6240}
1019
+ \herset{midnight-yt-mf}{0.606}
1020
+ \herset{midnight-yt-mfsd}{0.002}
1021
+ \herset{midnight-yt-s1}{0.619}
1022
+ \herset{midnight-yt-s2}{0.627}
1023
+ \herset{midnight-yt-s3}{0.626}
1024
+ \herset{midnight-probe}{0.690}
1025
+ \herset{midnightcm-yy}{0.811}
1026
+ \herset{midnightcm-yy-sd}{0.011}
1027
+ \herset{midnightcm-yy-v}{0.8114}
1028
+ \herset{midnightcm-yy-mf}{0.853}
1029
+ \herset{midnightcm-yy-mfsd}{0.007}
1030
+ \herset{midnightcm-yy-s1}{0.799}
1031
+ \herset{midnightcm-yy-s2}{0.821}
1032
+ \herset{midnightcm-yy-s3}{0.814}
1033
+ \herset{midnightcm-tt}{0.610}
1034
+ \herset{midnightcm-tt-sd}{0.008}
1035
+ \herset{midnightcm-tt-v}{0.6105}
1036
+ \herset{midnightcm-tt-mf}{0.632}
1037
+ \herset{midnightcm-tt-mfsd}{0.004}
1038
+ \herset{midnightcm-tt-s1}{0.602}
1039
+ \herset{midnightcm-tt-s2}{0.611}
1040
+ \herset{midnightcm-tt-s3}{0.618}
1041
+ \herset{midnightcm-ty}{0.734}
1042
+ \herset{midnightcm-ty-sd}{0.021}
1043
+ \herset{midnightcm-ty-v}{0.7337}
1044
+ \herset{midnightcm-ty-mf}{0.700}
1045
+ \herset{midnightcm-ty-mfsd}{0.012}
1046
+ \herset{midnightcm-ty-s1}{0.757}
1047
+ \herset{midnightcm-ty-s2}{0.727}
1048
+ \herset{midnightcm-ty-s3}{0.717}
1049
+ \herset{midnightcm-yt}{0.638}
1050
+ \herset{midnightcm-yt-sd}{0.004}
1051
+ \herset{midnightcm-yt-v}{0.6376}
1052
+ \herset{midnightcm-yt-mf}{0.627}
1053
+ \herset{midnightcm-yt-mfsd}{0.004}
1054
+ \herset{midnightcm-yt-s1}{0.641}
1055
+ \herset{midnightcm-yt-s2}{0.638}
1056
+ \herset{midnightcm-yt-s3}{0.633}
1057
+ \herset{midnightcm-probe}{0.705}
1058
+ \herset{midnight1um-yy}{0.801}
1059
+ \herset{midnight1um-yy-sd}{0.006}
1060
+ \herset{midnight1um-yy-v}{0.8013}
1061
+ \herset{midnight1um-yy-mf}{0.825}
1062
+ \herset{midnight1um-yy-mfsd}{0.022}
1063
+ \herset{midnight1um-yy-s1}{0.795}
1064
+ \herset{midnight1um-yy-s2}{0.807}
1065
+ \herset{midnight1um-yy-s3}{0.801}
1066
+ \herset{midnight1um-tt}{0.586}
1067
+ \herset{midnight1um-tt-sd}{0.013}
1068
+ \herset{midnight1um-tt-v}{0.5858}
1069
+ \herset{midnight1um-tt-mf}{0.598}
1070
+ \herset{midnight1um-tt-mfsd}{0.013}
1071
+ \herset{midnight1um-tt-s1}{0.598}
1072
+ \herset{midnight1um-tt-s2}{0.588}
1073
+ \herset{midnight1um-tt-s3}{0.572}
1074
+ \herset{midnight1um-ty}{0.724}
1075
+ \herset{midnight1um-ty-sd}{0.027}
1076
+ \herset{midnight1um-ty-v}{0.7243}
1077
+ \herset{midnight1um-ty-mf}{0.681}
1078
+ \herset{midnight1um-ty-mfsd}{0.019}
1079
+ \herset{midnight1um-ty-s1}{0.740}
1080
+ \herset{midnight1um-ty-s2}{0.740}
1081
+ \herset{midnight1um-ty-s3}{0.693}
1082
+ \herset{midnight1um-yt}{0.609}
1083
+ \herset{midnight1um-yt-sd}{0.005}
1084
+ \herset{midnight1um-yt-v}{0.6087}
1085
+ \herset{midnight1um-yt-mf}{0.601}
1086
+ \herset{midnight1um-yt-mfsd}{0.003}
1087
+ \herset{midnight1um-yt-s1}{0.615}
1088
+ \herset{midnight1um-yt-s2}{0.605}
1089
+ \herset{midnight1um-yt-s3}{0.606}
1090
+ \herset{hoptaug-yy}{0.898}
1091
+ \herset{hoptaug-yy-sd}{0.010}
1092
+ \herset{hoptaug-yy-v}{0.8978}
1093
+ \herset{hoptaug-yy-mf}{0.912}
1094
+ \herset{hoptaug-yy-mfsd}{0.006}
1095
+ \herset{hoptaug-yy-s1}{0.886}
1096
+ \herset{hoptaug-yy-s2}{0.906}
1097
+ \herset{hoptaug-yy-s3}{0.901}
1098
+ \herset{hoptaug-tt}{0.669}
1099
+ \herset{hoptaug-tt-sd}{0.023}
1100
+ \herset{hoptaug-tt-v}{0.6685}
1101
+ \herset{hoptaug-tt-mf}{0.683}
1102
+ \herset{hoptaug-tt-mfsd}{0.015}
1103
+ \herset{hoptaug-tt-s1}{0.691}
1104
+ \herset{hoptaug-tt-s2}{0.671}
1105
+ \herset{hoptaug-tt-s3}{0.644}
1106
+ \herset{hoptaug-ty}{0.798}
1107
+ \herset{hoptaug-ty-sd}{0.017}
1108
+ \herset{hoptaug-ty-v}{0.7977}
1109
+ \herset{hoptaug-ty-mf}{0.747}
1110
+ \herset{hoptaug-ty-mfsd}{0.019}
1111
+ \herset{hoptaug-ty-s1}{0.812}
1112
+ \herset{hoptaug-ty-s2}{0.779}
1113
+ \herset{hoptaug-ty-s3}{0.802}
1114
+ \herset{hoptaug-yt}{0.656}
1115
+ \herset{hoptaug-yt-sd}{0.001}
1116
+ \herset{hoptaug-yt-v}{0.6562}
1117
+ \herset{hoptaug-yt-mf}{0.642}
1118
+ \herset{hoptaug-yt-mfsd}{0.002}
1119
+ \herset{hoptaug-yt-s1}{0.655}
1120
+ \herset{hoptaug-yt-s2}{0.658}
1121
+ \herset{hoptaug-yt-s3}{0.656}
1122
+ \herset{hoptrep-yy}{0.895}
1123
+ \herset{hoptrep-yy-sd}{0.014}
1124
+ \herset{hoptrep-yy-v}{0.8954}
1125
+ \herset{hoptrep-yy-mf}{0.912}
1126
+ \herset{hoptrep-yy-mfsd}{0.006}
1127
+ \herset{hoptrep-yy-s1}{0.879}
1128
+ \herset{hoptrep-yy-s2}{0.900}
1129
+ \herset{hoptrep-yy-s3}{0.907}
1130
+ \herset{hoptrep-tt}{0.668}
1131
+ \herset{hoptrep-tt-sd}{0.015}
1132
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1133
+ \herset{hoptrep-tt-mf}{0.678}
1134
+ \herset{hoptrep-tt-mfsd}{0.014}
1135
+ \herset{hoptrep-tt-s1}{0.677}
1136
+ \herset{hoptrep-tt-s2}{0.652}
1137
+ \herset{hoptrep-tt-s3}{0.676}
1138
+ \herset{hoptrep-ty}{0.787}
1139
+ \herset{hoptrep-ty-sd}{0.031}
1140
+ \herset{hoptrep-ty-v}{0.7871}
1141
+ \herset{hoptrep-ty-mf}{0.751}
1142
+ \herset{hoptrep-ty-mfsd}{0.016}
1143
+ \herset{hoptrep-ty-s1}{0.814}
1144
+ \herset{hoptrep-ty-s2}{0.753}
1145
+ \herset{hoptrep-ty-s3}{0.793}
1146
+ \herset{hoptrep-yt}{0.656}
1147
+ \herset{hoptrep-yt-sd}{0.005}
1148
+ \herset{hoptrep-yt-v}{0.6562}
1149
+ \herset{hoptrep-yt-mf}{0.642}
1150
+ \herset{hoptrep-yt-mfsd}{0.003}
1151
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1152
+ \herset{hoptrep-yt-s2}{0.654}
1153
+ \herset{hoptrep-yt-s3}{0.662}
1154
+ \herset{hoptcard-yy}{0.887}
1155
+ \herset{hoptcard-yy-sd}{0.007}
1156
+ \herset{hoptcard-yy-v}{0.8868}
1157
+ \herset{hoptcard-yy-mf}{0.906}
1158
+ \herset{hoptcard-yy-mfsd}{0.006}
1159
+ \herset{hoptcard-yy-s1}{0.879}
1160
+ \herset{hoptcard-yy-s2}{0.893}
1161
+ \herset{hoptcard-yy-s3}{0.888}
1162
+ \herset{hoptcard-tt}{0.676}
1163
+ \herset{hoptcard-tt-sd}{0.016}
1164
+ \herset{hoptcard-tt-v}{0.6755}
1165
+ \herset{hoptcard-tt-mf}{0.696}
1166
+ \herset{hoptcard-tt-mfsd}{0.013}
1167
+ \herset{hoptcard-tt-s1}{0.694}
1168
+ \herset{hoptcard-tt-s2}{0.663}
1169
+ \herset{hoptcard-tt-s3}{0.669}
1170
+ \herset{hoptcard-ty}{0.810}
1171
+ \herset{hoptcard-ty-sd}{0.012}
1172
+ \herset{hoptcard-ty-v}{0.8100}
1173
+ \herset{hoptcard-ty-mf}{0.764}
1174
+ \herset{hoptcard-ty-mfsd}{0.010}
1175
+ \herset{hoptcard-ty-s1}{0.799}
1176
+ \herset{hoptcard-ty-s2}{0.810}
1177
+ \herset{hoptcard-ty-s3}{0.822}
1178
+ \herset{hoptcard-yt}{0.653}
1179
+ \herset{hoptcard-yt-sd}{0.008}
1180
+ \herset{hoptcard-yt-v}{0.6531}
1181
+ \herset{hoptcard-yt-mf}{0.642}
1182
+ \herset{hoptcard-yt-mfsd}{0.007}
1183
+ \herset{hoptcard-yt-s1}{0.645}
1184
+ \herset{hoptcard-yt-s2}{0.655}
1185
+ \herset{hoptcard-yt-s3}{0.660}
1186
+ \herset{hoptcard-probe}{0.581}
1187
+ \herset{hoptcm-yy}{0.893}
1188
+ \herset{hoptcm-yy-sd}{0.016}
1189
+ \herset{hoptcm-yy-v}{0.8925}
1190
+ \herset{hoptcm-yy-mf}{0.915}
1191
+ \herset{hoptcm-yy-mfsd}{0.002}
1192
+ \herset{hoptcm-yy-s1}{0.875}
1193
+ \herset{hoptcm-yy-s2}{0.904}
1194
+ \herset{hoptcm-yy-s3}{0.899}
1195
+ \herset{hoptcm-tt}{0.672}
1196
+ \herset{hoptcm-tt-sd}{0.018}
1197
+ \herset{hoptcm-tt-v}{0.6723}
1198
+ \herset{hoptcm-tt-mf}{0.688}
1199
+ \herset{hoptcm-tt-mfsd}{0.011}
1200
+ \herset{hoptcm-tt-s1}{0.671}
1201
+ \herset{hoptcm-tt-s2}{0.655}
1202
+ \herset{hoptcm-tt-s3}{0.691}
1203
+ \herset{hoptcm-ty}{0.803}
1204
+ \herset{hoptcm-ty-sd}{0.025}
1205
+ \herset{hoptcm-ty-v}{0.8028}
1206
+ \herset{hoptcm-ty-mf}{0.764}
1207
+ \herset{hoptcm-ty-mfsd}{0.011}
1208
+ \herset{hoptcm-ty-s1}{0.774}
1209
+ \herset{hoptcm-ty-s2}{0.815}
1210
+ \herset{hoptcm-ty-s3}{0.819}
1211
+ \herset{hoptcm-yt}{0.663}
1212
+ \herset{hoptcm-yt-sd}{0.006}
1213
+ \herset{hoptcm-yt-v}{0.6630}
1214
+ \herset{hoptcm-yt-mf}{0.649}
1215
+ \herset{hoptcm-yt-mfsd}{0.005}
1216
+ \herset{hoptcm-yt-s1}{0.657}
1217
+ \herset{hoptcm-yt-s2}{0.665}
1218
+ \herset{hoptcm-yt-s3}{0.667}
1219
+ \herset{hoptcm-probe}{0.592}
1220
+ \herset{hopt1um-yy}{0.909}
1221
+ \herset{hopt1um-yy-sd}{0.007}
1222
+ \herset{hopt1um-yy-v}{0.9088}
1223
+ \herset{hopt1um-yy-mf}{0.925}
1224
+ \herset{hopt1um-yy-mfsd}{0.008}
1225
+ \herset{hopt1um-yy-s1}{0.904}
1226
+ \herset{hopt1um-yy-s2}{0.906}
1227
+ \herset{hopt1um-yy-s3}{0.916}
1228
+ \herset{hopt1um-tt}{0.659}
1229
+ \herset{hopt1um-tt-sd}{0.015}
1230
+ \herset{hopt1um-tt-v}{0.6591}
1231
+ \herset{hopt1um-tt-mf}{0.677}
1232
+ \herset{hopt1um-tt-mfsd}{0.013}
1233
+ \herset{hopt1um-tt-s1}{0.666}
1234
+ \herset{hopt1um-tt-s2}{0.641}
1235
+ \herset{hopt1um-tt-s3}{0.670}
1236
+ \herset{hopt1um-ty}{0.803}
1237
+ \herset{hopt1um-ty-sd}{0.011}
1238
+ \herset{hopt1um-ty-v}{0.8033}
1239
+ \herset{hopt1um-ty-mf}{0.764}
1240
+ \herset{hopt1um-ty-mfsd}{0.020}
1241
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1242
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1243
+ \herset{hopt1um-ty-s3}{0.803}
1244
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1245
+ \herset{hopt1um-yt-sd}{0.007}
1246
+ \herset{hopt1um-yt-v}{0.6419}
1247
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1248
+ \herset{hopt1um-yt-mfsd}{0.004}
1249
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1250
+ \herset{hopt1um-yt-s2}{0.642}
1251
+ \herset{hopt1um-yt-s3}{0.649}
1252
+ \herset{lb-n}{11}
1253
+ \herset{lb-n-path}{6}
1254
+ \herset{lb-pathrank-yy}{4}
1255
+ \herset{lb-pathrank-tt}{5}
1256
+ \herset{lb-pathrank-ty}{3}
1257
+ \herset{lb-pathrank-yt}{6}
1258
+ \herset{lb-n-small}{5}
1259
+ \herset{lb-smallrank-yy}{1}
1260
+ \herset{lb-smallrank-tt}{1}
1261
+ \herset{lb-smallrank-ty}{1}
1262
+ \herset{lb-smallrank-yt}{1}
1263
+ \herset{par-phikon}{86M}
1264
+ \herset{gmac-phikon}{17.6}
1265
+ \herset{parn-phikon}{8.58e+07}
1266
+ \herset{cpu-phikon}{23.0}
1267
+ \herset{lb-rank-phikon-yy}{2}
1268
+ \herset{lb-rank-phikon-tt}{2}
1269
+ \herset{lb-rank-phikon-ty}{1}
1270
+ \herset{lb-rank-phikon-yt}{1}
1271
+ \herset{par-hoptcard}{1.1B}
1272
+ \herset{gmac-hoptcard}{304.2}
1273
+ \herset{parn-hoptcard}{1.135e+09}
1274
+ \herset{cpu-hoptcard}{312.3}
1275
+ \herset{lb-rank-hoptcard-yy}{1}
1276
+ \herset{lb-rank-hoptcard-tt}{1}
1277
+ \herset{lb-rank-hoptcard-ty}{2}
1278
+ \herset{lb-rank-hoptcard-yt}{3}
1279
+ \herset{par-d18s40k}{86M}
1280
+ \herset{gmac-d18s40k}{17.6}
1281
+ \herset{parn-d18s40k}{8.58e+07}
1282
+ \herset{cpu-d18s40k}{23.0}
1283
+ \herset{lb-rank-d18s40k-yy}{5}
1284
+ \herset{lb-rank-d18s40k-tt}{5}
1285
+ \herset{lb-rank-d18s40k-ty}{3}
1286
+ \herset{lb-rank-d18s40k-yt}{4}
1287
+ \herset{par-d16final}{22M}
1288
+ \herset{gmac-d16final}{4.6}
1289
+ \herset{parn-d16final}{2.167e+07}
1290
+ \herset{cpu-d16final}{8.4}
1291
+ \herset{lb-rank-d16final-yy}{4}
1292
+ \herset{lb-rank-d16final-tt}{6}
1293
+ \herset{lb-rank-d16final-ty}{4}
1294
+ \herset{lb-rank-d16final-yt}{7}
1295
+ \herset{par-virchow2}{631M}
1296
+ \herset{gmac-virchow2}{170.1}
1297
+ \herset{parn-virchow2}{6.312e+08}
1298
+ \herset{lb-rank-virchow2-yy}{3}
1299
+ \herset{lb-rank-virchow2-tt}{4}
1300
+ \herset{lb-rank-virchow2-ty}{5}
1301
+ \herset{lb-rank-virchow2-yt}{2}
1302
+ \herset{par-midnightcm}{1.1B}
1303
+ \herset{gmac-midnightcm}{299.4}
1304
+ \herset{parn-midnightcm}{1.135e+09}
1305
+ \herset{cpu-midnightcm}{312.3}
1306
+ \herset{lb-rank-midnightcm-yy}{6}
1307
+ \herset{lb-rank-midnightcm-tt}{7}
1308
+ \herset{lb-rank-midnightcm-ty}{6}
1309
+ \herset{lb-rank-midnightcm-yt}{5}
1310
+ \herset{par-hibou}{86M}
1311
+ \herset{gmac-hibou}{23.5}
1312
+ \herset{parn-hibou}{8.572e+07}
1313
+ \herset{lb-rank-hibou-yy}{7}
1314
+ \herset{lb-rank-hibou-tt}{3}
1315
+ \herset{lb-rank-hibou-ty}{7}
1316
+ \herset{lb-rank-hibou-yt}{6}
1317
+ \herset{par-d13}{22M}
1318
+ \herset{gmac-d13}{4.6}
1319
+ \herset{parn-d13}{2.167e+07}
1320
+ \herset{cpu-d13}{8.4}
1321
+ \herset{lb-rank-d13-yy}{8}
1322
+ \herset{lb-rank-d13-tt}{8}
1323
+ \herset{lb-rank-d13-ty}{8}
1324
+ \herset{lb-rank-d13-yt}{10}
1325
+ \herset{par-rn50}{26M}
1326
+ \herset{gmac-rn50}{4.1}
1327
+ \herset{parn-rn50}{2.56e+07}
1328
+ \herset{lb-rank-rn50-yy}{11}
1329
+ \herset{lb-rank-rn50-tt}{10}
1330
+ \herset{lb-rank-rn50-ty}{9}
1331
+ \herset{lb-rank-rn50-yt}{9}
1332
+ \herset{par-dinov2s}{22M}
1333
+ \herset{gmac-dinov2s}{6.1}
1334
+ \herset{parn-dinov2s}{2.162e+07}
1335
+ \herset{lb-rank-dinov2s-yy}{10}
1336
+ \herset{lb-rank-dinov2s-tt}{11}
1337
+ \herset{lb-rank-dinov2s-ty}{10}
1338
+ \herset{lb-rank-dinov2s-yt}{8}
1339
+ \herset{par-s16final}{22M}
1340
+ \herset{gmac-s16final}{4.6}
1341
+ \herset{parn-s16final}{2.167e+07}
1342
+ \herset{cpu-s16final}{8.4}
1343
+ \herset{lb-rank-s16final-yy}{9}
1344
+ \herset{lb-rank-s16final-tt}{9}
1345
+ \herset{lb-rank-s16final-ty}{11}
1346
+ \herset{lb-rank-s16final-yt}{11}
1347
+ \herset{gmacx-phikon}{3.8}
1348
+ \herset{parx-phikon}{4.0}
1349
+ \herset{cpux-phikon}{2.7}
1350
+ \herset{cpuhour-phikon}{157}
1351
+ \herset{gmacx-hoptcard}{66}
1352
+ \herset{parx-hoptcard}{52}
1353
+ \herset{cpux-hoptcard}{37}
1354
+ \herset{cpuhour-hoptcard}{12}
1355
+ \herset{gmacx-d18s40k}{3.8}
1356
+ \herset{parx-d18s40k}{4.0}
1357
+ \herset{cpux-d18s40k}{2.7}
1358
+ \herset{cpuhour-d18s40k}{157}
1359
+ \herset{gmacx-d16final}{1.0}
1360
+ \herset{parx-d16final}{1.0}
1361
+ \herset{cpux-d16final}{1.0}
1362
+ \herset{cpuhour-d16final}{427}
1363
+ \herset{gmacx-virchow2}{37}
1364
+ \herset{parx-virchow2}{29}
1365
+ \herset{gmacx-midnightcm}{65}
1366
+ \herset{parx-midnightcm}{52}
1367
+ \herset{cpux-midnightcm}{37}
1368
+ \herset{cpuhour-midnightcm}{12}
1369
+ \herset{gmacx-hibou}{5.1}
1370
+ \herset{parx-hibou}{4.0}
1371
+ \herset{gmacx-d13}{1.0}
1372
+ \herset{parx-d13}{1.0}
1373
+ \herset{cpux-d13}{1.0}
1374
+ \herset{cpuhour-d13}{427}
1375
+ \herset{gmacx-rn50}{0.9}
1376
+ \herset{parx-rn50}{1.2}
1377
+ \herset{gmacx-dinov2s}{1.3}
1378
+ \herset{parx-dinov2s}{1.0}
1379
+ \herset{gmacx-s16final}{1.0}
1380
+ \herset{parx-s16final}{1.0}
1381
+ \herset{cpux-s16final}{1.0}
1382
+ \herset{cpuhour-s16final}{427}
1383
+ \herset{dot-rows}{47}
1384
+ \herset{pd-s16final-dinov2s-yy}{+0.048}
1385
+ \herset{pd-s16final-dinov2s-yy-k}{2/3}
1386
+ \herset{pd-s16final-dinov2s-tt}{+0.088}
1387
+ \herset{pd-s16final-dinov2s-tt-k}{3/3}
1388
+ \herset{pd-s16final-dinov2s-ty}{$-$0.005}
1389
+ \herset{pd-s16final-dinov2s-ty-k}{2/3}
1390
+ \herset{pd-s16final-dinov2s-yt}{$-$0.056}
1391
+ \herset{pd-s16final-dinov2s-yt-k}{0/3}
1392
+ \herset{pd-s16final-s16s5-yy}{+0.041}
1393
+ \herset{pd-s16final-s16s5-yy-k}{3/3}
1394
+ \herset{pd-s16final-s16s5-tt}{+0.019}
1395
+ \herset{pd-s16final-s16s5-tt-k}{2/3}
1396
+ \herset{pd-s16final-s16s5-ty}{$-$0.092}
1397
+ \herset{pd-s16final-s16s5-ty-k}{0/3}
1398
+ \herset{pd-s16final-s16s5-yt}{$-$0.002}
1399
+ \herset{pd-s16final-s16s5-yt-k}{1/3}
1400
+ \herset{pd-s16final-s16s20-yy}{+0.029}
1401
+ \herset{pd-s16final-s16s20-yy-k}{2/3}
1402
+ \herset{pd-s16final-s16s20-tt}{+0.022}
1403
+ \herset{pd-s16final-s16s20-tt-k}{3/3}
1404
+ \herset{pd-s16final-s16s20-ty}{$-$0.033}
1405
+ \herset{pd-s16final-s16s20-ty-k}{1/3}
1406
+ \herset{pd-s16final-s16s20-yt}{$-$0.025}
1407
+ \herset{pd-s16final-s16s20-yt-k}{0/3}
1408
+ \herset{pd-midnight-d13-yy}{+0.035}
1409
+ \herset{pd-midnight-d13-yy-k}{3/3}
1410
+ \herset{pd-midnight-d13-tt}{+0.007}
1411
+ \herset{pd-midnight-d13-tt-k}{2/3}
1412
+ \herset{pd-midnight-d13-ty}{+0.015}
1413
+ \herset{pd-midnight-d13-ty-k}{2/3}
1414
+ \herset{pd-midnight-d13-yt}{+0.079}
1415
+ \herset{pd-midnight-d13-yt-k}{3/3}
1416
+ \herset{pd-hoptcard-d14-yy}{+0.080}
1417
+ \herset{pd-hoptcard-d14-yy-k}{3/3}
1418
+ \herset{pd-hoptcard-d14-tt}{+0.007}
1419
+ \herset{pd-hoptcard-d14-tt-k}{2/3}
1420
+ \herset{pd-hoptcard-d14-ty}{+0.094}
1421
+ \herset{pd-hoptcard-d14-ty-k}{3/3}
1422
+ \herset{pd-hoptcard-d14-yt}{+0.080}
1423
+ \herset{pd-hoptcard-d14-yt-k}{3/3}
1424
+ \herset{pd-hoptcard-d16final-yy}{+0.067}
1425
+ \herset{pd-hoptcard-d16final-yy-k}{3/3}
1426
+ \herset{pd-hoptcard-d16final-tt}{+0.053}
1427
+ \herset{pd-hoptcard-d16final-tt-k}{3/3}
1428
+ \herset{pd-hoptcard-d16final-ty}{+0.066}
1429
+ \herset{pd-hoptcard-d16final-ty-k}{3/3}
1430
+ \herset{pd-hoptcard-d16final-yt}{+0.060}
1431
+ \herset{pd-hoptcard-d16final-yt-k}{3/3}
1432
+ \herset{pd-d13-s16s50-yy}{$-$0.009}
1433
+ \herset{pd-d13-s16s50-yy-k}{1/3}
1434
+ \herset{pd-d13-s16s50-tt}{$-$0.019}
1435
+ \herset{pd-d13-s16s50-tt-k}{0/3}
1436
+ \herset{pd-d13-s16s50-ty}{+0.151}
1437
+ \herset{pd-d13-s16s50-ty-k}{3/3}
1438
+ \herset{pd-d13-s16s50-yt}{+0.017}
1439
+ \herset{pd-d13-s16s50-yt-k}{3/3}
1440
+ \herset{pd-d14-s16s50-yy}{+0.026}
1441
+ \herset{pd-d14-s16s50-yy-k}{2/3}
1442
+ \herset{pd-d14-s16s50-tt}{+0.060}
1443
+ \herset{pd-d14-s16s50-tt-k}{3/3}
1444
+ \herset{pd-d14-s16s50-ty}{+0.166}
1445
+ \herset{pd-d14-s16s50-ty-k}{3/3}
1446
+ \herset{pd-d14-s16s50-yt}{+0.045}
1447
+ \herset{pd-d14-s16s50-yt-k}{3/3}
1448
+ \herset{pd-d14-d13-yy}{+0.035}
1449
+ \herset{pd-d14-d13-yy-k}{3/3}
1450
+ \herset{pd-d14-d13-tt}{+0.079}
1451
+ \herset{pd-d14-d13-tt-k}{3/3}
1452
+ \herset{pd-d14-d13-ty}{+0.015}
1453
+ \herset{pd-d14-d13-ty-k}{2/3}
1454
+ \herset{pd-d14-d13-yt}{+0.028}
1455
+ \herset{pd-d14-d13-yt-k}{3/3}
1456
+ \herset{pd-d15final-d15rand-yy}{+0.031}
1457
+ \herset{pd-d15final-d15rand-yy-k}{3/3}
1458
+ \herset{pd-d15final-d15rand-tt}{+0.040}
1459
+ \herset{pd-d15final-d15rand-tt-k}{3/3}
1460
+ \herset{pd-d15final-d15rand-ty}{+0.031}
1461
+ \herset{pd-d15final-d15rand-ty-k}{2/3}
1462
+ \herset{pd-d15final-d15rand-yt}{+0.024}
1463
+ \herset{pd-d15final-d15rand-yt-k}{3/3}
1464
+ \herset{pd-d16final-d16rand-yy}{+0.027}
1465
+ \herset{pd-d16final-d16rand-yy-k}{3/3}
1466
+ \herset{pd-d16final-d16rand-tt}{+0.031}
1467
+ \herset{pd-d16final-d16rand-tt-k}{3/3}
1468
+ \herset{pd-d16final-d16rand-ty}{+0.006}
1469
+ \herset{pd-d16final-d16rand-ty-k}{2/3}
1470
+ \herset{pd-d16final-d16rand-yt}{+0.030}
1471
+ \herset{pd-d16final-d16rand-yt-k}{3/3}
1472
+ \herset{pd-d16final-d16s50k-yy}{+0.005}
1473
+ \herset{pd-d16final-d16s50k-yy-k}{2/3}
1474
+ \herset{pd-d16final-d16s50k-tt}{$-$0.013}
1475
+ \herset{pd-d16final-d16s50k-tt-k}{1/3}
1476
+ \herset{pd-d16final-d16s50k-ty}{+0.005}
1477
+ \herset{pd-d16final-d16s50k-ty-k}{2/3}
1478
+ \herset{pd-d16final-d16s50k-yt}{$-$0.029}
1479
+ \herset{pd-d16final-d16s50k-yt-k}{0/3}
1480
+ \herset{pd-d16final-s16final-yy}{+0.052}
1481
+ \herset{pd-d16final-s16final-yy-k}{3/3}
1482
+ \herset{pd-d16final-s16final-tt}{+0.034}
1483
+ \herset{pd-d16final-s16final-tt-k}{3/3}
1484
+ \herset{pd-d16final-s16final-ty}{+0.160}
1485
+ \herset{pd-d16final-s16final-ty-k}{3/3}
1486
+ \herset{pd-d16final-s16final-yt}{+0.072}
1487
+ \herset{pd-d16final-s16final-yt-k}{3/3}
1488
+ \herset{pd-b16s40-s16s40-yy}{+0.001}
1489
+ \herset{pd-b16s40-s16s40-yy-k}{1/3}
1490
+ \herset{pd-b16s40-s16s40-tt}{$-$0.013}
1491
+ \herset{pd-b16s40-s16s40-tt-k}{1/3}
1492
+ \herset{pd-b16s40-s16s40-ty}{+0.100}
1493
+ \herset{pd-b16s40-s16s40-ty-k}{3/3}
1494
+ \herset{pd-b16s40-s16s40-yt}{+0.033}
1495
+ \herset{pd-b16s40-s16s40-yt-k}{3/3}
1496
+ \herset{pd-d18s40k-b16s40-yy}{+0.024}
1497
+ \herset{pd-d18s40k-b16s40-yy-k}{3/3}
1498
+ \herset{pd-d18s40k-b16s40-tt}{+0.026}
1499
+ \herset{pd-d18s40k-b16s40-tt-k}{3/3}
1500
+ \herset{pd-d18s40k-b16s40-ty}{+0.111}
1501
+ \herset{pd-d18s40k-b16s40-ty-k}{3/3}
1502
+ \herset{pd-d18s40k-b16s40-yt}{+0.093}
1503
+ \herset{pd-d18s40k-b16s40-yt-k}{3/3}
1504
+ \herset{pd-d18s40k-d18s45k-yy}{+0.041}
1505
+ \herset{pd-d18s40k-d18s45k-yy-k}{3/3}
1506
+ \herset{pd-d18s40k-d18s45k-tt}{0.000}
1507
+ \herset{pd-d18s40k-d18s45k-tt-k}{2/3}
1508
+ \herset{pd-d18s40k-d18s45k-ty}{+0.013}
1509
+ \herset{pd-d18s40k-d18s45k-ty-k}{2/3}
1510
+ \herset{pd-d18s40k-d18s45k-yt}{+0.019}
1511
+ \herset{pd-d18s40k-d18s45k-yt-k}{3/3}
1512
+ \herset{pd-d18s40k-d18s50k-yy}{+0.015}
1513
+ \herset{pd-d18s40k-d18s50k-yy-k}{2/3}
1514
+ \herset{pd-d18s40k-d18s50k-tt}{+0.018}
1515
+ \herset{pd-d18s40k-d18s50k-tt-k}{3/3}
1516
+ \herset{pd-d18s40k-d18s50k-ty}{+0.021}
1517
+ \herset{pd-d18s40k-d18s50k-ty-k}{3/3}
1518
+ \herset{pd-d18s40k-d18s50k-yt}{+0.027}
1519
+ \herset{pd-d18s40k-d18s50k-yt-k}{3/3}
1520
+ \herset{pd-d18s40k-d16final-yy}{$-$0.002}
1521
+ \herset{pd-d18s40k-d16final-yy-k}{2/3}
1522
+ \herset{pd-d18s40k-d16final-tt}{+0.010}
1523
+ \herset{pd-d18s40k-d16final-tt-k}{1/3}
1524
+ \herset{pd-d18s40k-d16final-ty}{+0.031}
1525
+ \herset{pd-d18s40k-d16final-ty-k}{3/3}
1526
+ \herset{pd-d18s40k-d16final-yt}{+0.048}
1527
+ \herset{pd-d18s40k-d16final-yt-k}{3/3}
1528
+ \herset{pd-d18s40k-phikon-yy}{$-$0.058}
1529
+ \herset{pd-d18s40k-phikon-yy-k}{0/3}
1530
+ \herset{pd-d18s40k-phikon-tt}{$-$0.036}
1531
+ \herset{pd-d18s40k-phikon-tt-k}{0/3}
1532
+ \herset{pd-d18s40k-phikon-ty}{$-$0.037}
1533
+ \herset{pd-d18s40k-phikon-ty-k}{0/3}
1534
+ \herset{pd-d18s40k-phikon-yt}{$-$0.020}
1535
+ \herset{pd-d18s40k-phikon-yt-k}{0/3}
1536
+ \herset{pd-d18s45k-d16final-yy}{$-$0.043}
1537
+ \herset{pd-d18s45k-d16final-yy-k}{0/3}
1538
+ \herset{pd-d18s45k-d16final-tt}{+0.010}
1539
+ \herset{pd-d18s45k-d16final-tt-k}{2/3}
1540
+ \herset{pd-d18s45k-d16final-ty}{+0.018}
1541
+ \herset{pd-d18s45k-d16final-ty-k}{2/3}
1542
+ \herset{pd-d18s45k-d16final-yt}{+0.028}
1543
+ \herset{pd-d18s45k-d16final-yt-k}{3/3}
1544
+ \herset{pd-d18s50k-d16final-yy}{$-$0.016}
1545
+ \herset{pd-d18s50k-d16final-yy-k}{1/3}
1546
+ \herset{pd-d18s50k-d16final-tt}{$-$0.008}
1547
+ \herset{pd-d18s50k-d16final-tt-k}{1/3}
1548
+ \herset{pd-d18s50k-d16final-ty}{+0.010}
1549
+ \herset{pd-d18s50k-d16final-ty-k}{3/3}
1550
+ \herset{pd-d18s50k-d16final-yt}{+0.021}
1551
+ \herset{pd-d18s50k-d16final-yt-k}{3/3}
1552
+ \herset{pd-hoptrep-hoptaug-yy}{$-$0.002}
1553
+ \herset{pd-hoptrep-hoptaug-yy-k}{1/3}
1554
+ \herset{pd-hoptrep-hoptaug-tt}{0.000}
1555
+ \herset{pd-hoptrep-hoptaug-tt-k}{1/3}
1556
+ \herset{pd-hoptrep-hoptaug-ty}{$-$0.011}
1557
+ \herset{pd-hoptrep-hoptaug-ty-k}{1/3}
1558
+ \herset{pd-hoptrep-hoptaug-yt}{0.000}
1559
+ \herset{pd-hoptrep-hoptaug-yt-k}{1/3}
1560
+ \herset{pd-hoptcard-hoptrep-yy}{$-$0.009}
1561
+ \herset{pd-hoptcard-hoptrep-yy-k}{0/3}
1562
+ \herset{pd-hoptcard-hoptrep-tt}{+0.007}
1563
+ \herset{pd-hoptcard-hoptrep-tt-k}{2/3}
1564
+ \herset{pd-hoptcard-hoptrep-ty}{+0.023}
1565
+ \herset{pd-hoptcard-hoptrep-ty-k}{2/3}
1566
+ \herset{pd-hoptcard-hoptrep-yt}{$-$0.003}
1567
+ \herset{pd-hoptcard-hoptrep-yt-k}{1/3}
1568
+ \herset{pd-hoptcm-hoptcard-yy}{+0.006}
1569
+ \herset{pd-hoptcm-hoptcard-yy-k}{2/3}
1570
+ \herset{pd-hoptcm-hoptcard-tt}{$-$0.003}
1571
+ \herset{pd-hoptcm-hoptcard-tt-k}{1/3}
1572
+ \herset{pd-hoptcm-hoptcard-ty}{$-$0.007}
1573
+ \herset{pd-hoptcm-hoptcard-ty-k}{1/3}
1574
+ \herset{pd-hoptcm-hoptcard-yt}{+0.010}
1575
+ \herset{pd-hoptcm-hoptcard-yt-k}{3/3}
1576
+ \herset{pd-hopt1um-hoptcard-yy}{+0.022}
1577
+ \herset{pd-hopt1um-hoptcard-yy-k}{3/3}
1578
+ \herset{pd-hopt1um-hoptcard-tt}{$-$0.016}
1579
+ \herset{pd-hopt1um-hoptcard-tt-k}{1/3}
1580
+ \herset{pd-hopt1um-hoptcard-ty}{$-$0.007}
1581
+ \herset{pd-hopt1um-hoptcard-ty-k}{1/3}
1582
+ \herset{pd-hopt1um-hoptcard-yt}{$-$0.011}
1583
+ \herset{pd-hopt1um-hoptcard-yt-k}{0/3}
1584
+ \herset{pd-midnightcm-midnight-yy}{+0.005}
1585
+ \herset{pd-midnightcm-midnight-yy-k}{2/3}
1586
+ \herset{pd-midnightcm-midnight-tt}{+0.013}
1587
+ \herset{pd-midnightcm-midnight-tt-k}{3/3}
1588
+ \herset{pd-midnightcm-midnight-ty}{+0.017}
1589
+ \herset{pd-midnightcm-midnight-ty-k}{2/3}
1590
+ \herset{pd-midnightcm-midnight-yt}{+0.014}
1591
+ \herset{pd-midnightcm-midnight-yt-k}{3/3}
1592
+ \herset{pd-midnight1um-midnight-yy}{$-$0.005}
1593
+ \herset{pd-midnight1um-midnight-yy-k}{1/3}
1594
+ \herset{pd-midnight1um-midnight-tt}{$-$0.011}
1595
+ \herset{pd-midnight1um-midnight-tt-k}{1/3}
1596
+ \herset{pd-midnight1um-midnight-ty}{+0.008}
1597
+ \herset{pd-midnight1um-midnight-ty-k}{2/3}
1598
+ \herset{pd-midnight1um-midnight-yt}{$-$0.015}
1599
+ \herset{pd-midnight1um-midnight-yt-k}{0/3}
1600
+ \herset{pd-hoptcard-midnightcm-yy}{+0.075}
1601
+ \herset{pd-hoptcard-midnightcm-yy-k}{3/3}
1602
+ \herset{pd-hoptcard-midnightcm-tt}{+0.065}
1603
+ \herset{pd-hoptcard-midnightcm-tt-k}{3/3}
1604
+ \herset{pd-hoptcard-midnightcm-ty}{+0.076}
1605
+ \herset{pd-hoptcard-midnightcm-ty-k}{3/3}
1606
+ \herset{pd-hoptcard-midnightcm-yt}{+0.016}
1607
+ \herset{pd-hoptcard-midnightcm-yt-k}{3/3}
1608
+ \herset{gap-d18s40k-yy}{26}
1609
+ \herset{gap-d18s40k-tt}{38}
1610
+ \herset{gap-d18s40k-ty}{76}
1611
+ \herset{gap-d18s40k-yt}{88}
1612
+ \herset{gap-d16final-yy}{44}
1613
+ \herset{gap-d16final-tt}{39}
1614
+ \herset{gap-d16final-ty}{71}
1615
+ \herset{gap-d16final-yt}{55}
1616
+ \herset{rand-costyale}{0.152}
1617
+ \herset{rand-costtcga}{0.023}
1618
+ \herset{dinov2s-costyale}{0.130}
1619
+ \herset{dinov2s-costtcga}{-0.075}
1620
+ \herset{rn50-costyale}{0.071}
1621
+ \herset{rn50-costtcga}{-0.009}
1622
+ \herset{s16s5-costyale}{0.050}
1623
+ \herset{s16s5-costtcga}{0.047}
1624
+ \herset{s16s20-costyale}{0.121}
1625
+ \herset{s16s20-costtcga}{0.022}
1626
+ \herset{s16s35-costyale}{0.243}
1627
+ \herset{s16s35-costtcga}{0.069}
1628
+ \herset{s16s40-costyale}{0.227}
1629
+ \herset{s16s40-costtcga}{0.106}
1630
+ \herset{s16s45-costyale}{0.173}
1631
+ \herset{s16s45-costtcga}{0.063}
1632
+ \herset{s16s50-costyale}{0.231}
1633
+ \herset{s16s50-costtcga}{0.080}
1634
+ \herset{s16s55-costyale}{0.188}
1635
+ \herset{s16s55-costtcga}{0.057}
1636
+ \herset{s16s60-costyale}{0.185}
1637
+ \herset{s16s60-costtcga}{0.064}
1638
+ \herset{s16s65-costyale}{0.206}
1639
+ \herset{s16s65-costtcga}{0.103}
1640
+ \herset{s16final-costyale}{0.183}
1641
+ \herset{s16final-costtcga}{0.069}
1642
+ \herset{b16s10-costyale}{0.185}
1643
+ \herset{b16s10-costtcga}{0.057}
1644
+ \herset{b16s35-costyale}{0.191}
1645
+ \herset{b16s35-costtcga}{0.036}
1646
+ \herset{b16s40-costyale}{0.128}
1647
+ \herset{b16s40-costtcga}{0.060}
1648
+ \herset{d13-costyale}{0.070}
1649
+ \herset{d13-costtcga}{0.045}
1650
+ \herset{d14-costyale}{0.091}
1651
+ \herset{d14-costtcga}{0.095}
1652
+ \herset{d15rand-costyale}{0.141}
1653
+ \herset{d15rand-costtcga}{0.019}
1654
+ \herset{d15s50k-costyale}{0.047}
1655
+ \herset{d15s50k-costtcga}{0.011}
1656
+ \herset{d15final-costyale}{0.141}
1657
+ \herset{d15final-costtcga}{0.035}
1658
+ \herset{d16rand-costyale}{0.053}
1659
+ \herset{d16rand-costtcga}{0.029}
1660
+ \herset{d16s50k-costyale}{0.075}
1661
+ \herset{d16s50k-costtcga}{0.015}
1662
+ \herset{d16final-costyale}{0.075}
1663
+ \herset{d16final-costtcga}{0.030}
1664
+ \herset{d18s40k-costyale}{0.042}
1665
+ \herset{d18s40k-costtcga}{-0.007}
1666
+ \herset{d18s45k-costyale}{0.014}
1667
+ \herset{d18s45k-costtcga}{0.011}
1668
+ \herset{d18s50k-costyale}{0.049}
1669
+ \herset{d18s50k-costtcga}{0.001}
1670
+ \herset{hibou-costyale}{0.062}
1671
+ \herset{hibou-costtcga}{0.013}
1672
+ \herset{phikon-costyale}{0.063}
1673
+ \herset{phikon-costtcga}{0.008}
1674
+ \herset{virchow2-costyale}{0.125}
1675
+ \herset{virchow2-costtcga}{-0.020}
1676
+ \herset{midnight-costyale}{0.090}
1677
+ \herset{midnight-costtcga}{-0.027}
1678
+ \herset{midnightcm-costyale}{0.078}
1679
+ \herset{midnightcm-costtcga}{-0.027}
1680
+ \herset{midnight1um-costyale}{0.077}
1681
+ \herset{midnight1um-costtcga}{-0.023}
1682
+ \herset{hoptaug-costyale}{0.100}
1683
+ \herset{hoptaug-costtcga}{0.012}
1684
+ \herset{hoptrep-costyale}{0.108}
1685
+ \herset{hoptrep-costtcga}{0.012}
1686
+ \herset{hoptcard-costyale}{0.077}
1687
+ \herset{hoptcard-costtcga}{0.022}
1688
+ \herset{hoptcm-costyale}{0.090}
1689
+ \herset{hoptcm-costtcga}{0.009}
1690
+ \herset{hopt1um-costyale}{0.106}
1691
+ \herset{hopt1um-costtcga}{0.017}
1692
+ \herset{ta-budget-yale-sslvits16final400tiles}{0.827}
1693
+ \herset{ta-budget-yale-sslvits16final400tiles-sd}{0.048}
1694
+ \herset{ta-budget-yale-sslvits16final400tiles-rank}{1}
1695
+ \herset{ta-budget-yale-p9finalall}{0.811}
1696
+ \herset{ta-budget-yale-p9finalall-sd}{0.026}
1697
+ \herset{ta-budget-yale-p9finalall-rank}{2}
1698
+ \herset{ta-budget-yale-p9finalall-pbest}{0.097}
1699
+ \herset{ta-budget-yale-n}{2}
1700
+ \herset{ta-budget-yale-ntop}{2}
1701
+ \herset{ta-eq-ish-hoptcard}{0.765}
1702
+ \herset{ta-eq-ish-hoptcard-sd}{0.107}
1703
+ \herset{ta-eq-ish-hoptcard-rank}{1}
1704
+ \herset{ta-eq-ish-s16final}{0.698}
1705
+ \herset{ta-eq-ish-s16final-sd}{0.072}
1706
+ \herset{ta-eq-ish-s16final-rank}{2}
1707
+ \herset{ta-eq-ish-s16final-pbest}{0.080}
1708
+ \herset{ta-eq-ish-d13}{0.690}
1709
+ \herset{ta-eq-ish-d13-sd}{0.103}
1710
+ \herset{ta-eq-ish-d13-rank}{3}
1711
+ \herset{ta-eq-ish-d13-pbest}{0.007}
1712
+ \herset{ta-eq-ish-midnight}{0.675}
1713
+ \herset{ta-eq-ish-midnight-sd}{0.119}
1714
+ \herset{ta-eq-ish-midnight-rank}{4}
1715
+ \herset{ta-eq-ish-midnight-pbest}{0.008}
1716
+ \herset{ta-eq-ish-n}{4}
1717
+ \herset{ta-eq-ish-ntop}{2}
1718
+ \herset{ta-her2-tcga-hoptcm}{0.669}
1719
+ \herset{ta-her2-tcga-hoptcm-sd}{0.072}
1720
+ \herset{ta-her2-tcga-hoptcm-rank}{1}
1721
+ \herset{ta-her2-tcga-hoptcm-prn}{0.001}
1722
+ \herset{ta-her2-tcga-hopt1um}{0.665}
1723
+ \herset{ta-her2-tcga-hopt1um-sd}{0.060}
1724
+ \herset{ta-her2-tcga-hopt1um-rank}{2}
1725
+ \herset{ta-her2-tcga-hopt1um-pbest}{0.376}
1726
+ \herset{ta-her2-tcga-hopt1um-prn}{0.002}
1727
+ \herset{ta-her2-tcga-d18s40k}{0.663}
1728
+ \herset{ta-her2-tcga-d18s40k-sd}{0.062}
1729
+ \herset{ta-her2-tcga-d18s40k-rank}{3}
1730
+ \herset{ta-her2-tcga-d18s40k-pbest}{0.312}
1731
+ \herset{ta-her2-tcga-d18s40k-prn}{0.001}
1732
+ \herset{ta-her2-tcga-hoptcard}{0.660}
1733
+ \herset{ta-her2-tcga-hoptcard-sd}{0.072}
1734
+ \herset{ta-her2-tcga-hoptcard-rank}{4}
1735
+ \herset{ta-her2-tcga-hoptcard-pbest}{0.278}
1736
+ \herset{ta-her2-tcga-hoptcard-prn}{0.001}
1737
+ \herset{ta-her2-tcga-hoptaug}{0.659}
1738
+ \herset{ta-her2-tcga-hoptaug-sd}{0.058}
1739
+ \herset{ta-her2-tcga-hoptaug-rank}{5}
1740
+ \herset{ta-her2-tcga-hoptaug-pbest}{0.097}
1741
+ \herset{ta-her2-tcga-hoptaug-prn}{0.001}
1742
+ \herset{ta-her2-tcga-d16final}{0.658}
1743
+ \herset{ta-her2-tcga-d16final-sd}{0.073}
1744
+ \herset{ta-her2-tcga-d16final-rank}{6}
1745
+ \herset{ta-her2-tcga-d16final-pbest}{0.312}
1746
+ \herset{ta-her2-tcga-d16final-prn}{0.002}
1747
+ \herset{ta-her2-tcga-phikon}{0.656}
1748
+ \herset{ta-her2-tcga-phikon-sd}{0.058}
1749
+ \herset{ta-her2-tcga-phikon-rank}{7}
1750
+ \herset{ta-her2-tcga-phikon-pbest}{0.216}
1751
+ \herset{ta-her2-tcga-phikon-prn}{0.007}
1752
+ \herset{ta-her2-tcga-d14}{0.653}
1753
+ \herset{ta-her2-tcga-d14-sd}{0.082}
1754
+ \herset{ta-her2-tcga-d14-rank}{8}
1755
+ \herset{ta-her2-tcga-d14-pbest}{0.188}
1756
+ \herset{ta-her2-tcga-d14-prn}{0.003}
1757
+ \herset{ta-her2-tcga-d16s50k}{0.651}
1758
+ \herset{ta-her2-tcga-d16s50k-sd}{0.050}
1759
+ \herset{ta-her2-tcga-d16s50k-rank}{9}
1760
+ \herset{ta-her2-tcga-d16s50k-pbest}{0.138}
1761
+ \herset{ta-her2-tcga-d16s50k-prn}{0.005}
1762
+ \herset{ta-her2-tcga-d18s45k}{0.645}
1763
+ \herset{ta-her2-tcga-d18s45k-sd}{0.064}
1764
+ \herset{ta-her2-tcga-d18s45k-rank}{10}
1765
+ \herset{ta-her2-tcga-d18s45k-pbest}{0.007}
1766
+ \herset{ta-her2-tcga-d18s45k-prn}{0.001}
1767
+ \herset{ta-her2-tcga-midnightcm}{0.630}
1768
+ \herset{ta-her2-tcga-midnightcm-sd}{0.048}
1769
+ \herset{ta-her2-tcga-midnightcm-rank}{11}
1770
+ \herset{ta-her2-tcga-midnightcm-pbest}{0.053}
1771
+ \herset{ta-her2-tcga-midnightcm-prn}{0.019}
1772
+ \herset{ta-her2-tcga-b16s40}{0.621}
1773
+ \herset{ta-her2-tcga-b16s40-sd}{0.069}
1774
+ \herset{ta-her2-tcga-b16s40-rank}{12}
1775
+ \herset{ta-her2-tcga-b16s40-pbest}{0.053}
1776
+ \herset{ta-her2-tcga-b16s40-prn}{0.065}
1777
+ \herset{ta-her2-tcga-d13}{0.616}
1778
+ \herset{ta-her2-tcga-d13-sd}{0.040}
1779
+ \herset{ta-her2-tcga-d13-rank}{13}
1780
+ \herset{ta-her2-tcga-d13-pbest}{0.010}
1781
+ \herset{ta-her2-tcga-d13-prn}{0.080}
1782
+ \herset{ta-her2-tcga-s16s45}{0.612}
1783
+ \herset{ta-her2-tcga-s16s45-sd}{0.066}
1784
+ \herset{ta-her2-tcga-s16s45-rank}{14}
1785
+ \herset{ta-her2-tcga-s16s45-pbest}{0.005}
1786
+ \herset{ta-her2-tcga-s16s45-prn}{0.080}
1787
+ \herset{ta-her2-tcga-s16s35}{0.610}
1788
+ \herset{ta-her2-tcga-s16s35-sd}{0.056}
1789
+ \herset{ta-her2-tcga-s16s35-rank}{15}
1790
+ \herset{ta-her2-tcga-s16s35-pbest}{0.019}
1791
+ \herset{ta-her2-tcga-s16s35-prn}{0.042}
1792
+ \herset{ta-her2-tcga-midnight}{0.606}
1793
+ \herset{ta-her2-tcga-midnight-sd}{0.034}
1794
+ \herset{ta-her2-tcga-midnight-rank}{16}
1795
+ \herset{ta-her2-tcga-midnight-pbest}{0.007}
1796
+ \herset{ta-her2-tcga-midnight-prn}{0.080}
1797
+ \herset{ta-her2-tcga-hibou}{0.605}
1798
+ \herset{ta-her2-tcga-hibou-sd}{0.048}
1799
+ \herset{ta-her2-tcga-hibou-rank}{17}
1800
+ \herset{ta-her2-tcga-hibou-pbest}{0.005}
1801
+ \herset{ta-her2-tcga-hibou-prn}{0.080}
1802
+ \herset{ta-her2-tcga-midnight1um}{0.603}
1803
+ \herset{ta-her2-tcga-midnight1um-sd}{0.054}
1804
+ \herset{ta-her2-tcga-midnight1um-rank}{18}
1805
+ \herset{ta-her2-tcga-midnight1um-pbest}{0.003}
1806
+ \herset{ta-her2-tcga-midnight1um-prn}{0.216}
1807
+ \herset{ta-her2-tcga-s16s40}{0.597}
1808
+ \herset{ta-her2-tcga-s16s40-sd}{0.070}
1809
+ \herset{ta-her2-tcga-s16s40-rank}{19}
1810
+ \herset{ta-her2-tcga-s16s40-pbest}{0.014}
1811
+ \herset{ta-her2-tcga-s16s40-prn}{0.188}
1812
+ \herset{ta-her2-tcga-s16final}{0.595}
1813
+ \herset{ta-her2-tcga-s16final-sd}{0.052}
1814
+ \herset{ta-her2-tcga-s16final-rank}{20}
1815
+ \herset{ta-her2-tcga-s16final-pbest}{0.010}
1816
+ \herset{ta-her2-tcga-s16final-prn}{0.188}
1817
+ \herset{ta-her2-tcga-s16s65}{0.594}
1818
+ \herset{ta-her2-tcga-s16s65-sd}{0.061}
1819
+ \herset{ta-her2-tcga-s16s65-rank}{21}
1820
+ \herset{ta-her2-tcga-s16s65-pbest}{0.010}
1821
+ \herset{ta-her2-tcga-s16s65-prn}{0.246}
1822
+ \herset{ta-her2-tcga-s16s60}{0.592}
1823
+ \herset{ta-her2-tcga-s16s60-sd}{0.049}
1824
+ \herset{ta-her2-tcga-s16s60-rank}{22}
1825
+ \herset{ta-her2-tcga-s16s60-pbest}{0.010}
1826
+ \herset{ta-her2-tcga-s16s60-prn}{0.188}
1827
+ \herset{ta-her2-tcga-b16s10}{0.591}
1828
+ \herset{ta-her2-tcga-b16s10-sd}{0.050}
1829
+ \herset{ta-her2-tcga-b16s10-rank}{23}
1830
+ \herset{ta-her2-tcga-b16s10-pbest}{0.003}
1831
+ \herset{ta-her2-tcga-b16s10-prn}{0.138}
1832
+ \herset{ta-her2-tcga-s16s20}{0.591}
1833
+ \herset{ta-her2-tcga-s16s20-sd}{0.047}
1834
+ \herset{ta-her2-tcga-s16s20-rank}{24}
1835
+ \herset{ta-her2-tcga-s16s20-pbest}{0.007}
1836
+ \herset{ta-her2-tcga-s16s20-prn}{0.188}
1837
+ \herset{ta-her2-tcga-d16rand}{0.590}
1838
+ \herset{ta-her2-tcga-d16rand-sd}{0.079}
1839
+ \herset{ta-her2-tcga-d16rand-rank}{25}
1840
+ \herset{ta-her2-tcga-d16rand-pbest}{0.001}
1841
+ \herset{ta-her2-tcga-d16rand-prn}{0.246}
1842
+ \herset{ta-her2-tcga-b16s35}{0.590}
1843
+ \herset{ta-her2-tcga-b16s35-sd}{0.061}
1844
+ \herset{ta-her2-tcga-b16s35-rank}{26}
1845
+ \herset{ta-her2-tcga-b16s35-pbest}{0.002}
1846
+ \herset{ta-her2-tcga-b16s35-prn}{0.216}
1847
+ \herset{ta-her2-tcga-s16s55}{0.589}
1848
+ \herset{ta-her2-tcga-s16s55-sd}{0.036}
1849
+ \herset{ta-her2-tcga-s16s55-rank}{27}
1850
+ \herset{ta-her2-tcga-s16s55-pbest}{0.005}
1851
+ \herset{ta-her2-tcga-s16s55-prn}{0.138}
1852
+ \herset{ta-her2-tcga-s16s50}{0.587}
1853
+ \herset{ta-her2-tcga-s16s50-sd}{0.049}
1854
+ \herset{ta-her2-tcga-s16s50-rank}{28}
1855
+ \herset{ta-her2-tcga-s16s50-pbest}{0.002}
1856
+ \herset{ta-her2-tcga-s16s50-prn}{0.216}
1857
+ \herset{ta-her2-tcga-d15s50k}{0.572}
1858
+ \herset{ta-her2-tcga-d15s50k-sd}{0.043}
1859
+ \herset{ta-her2-tcga-d15s50k-rank}{29}
1860
+ \herset{ta-her2-tcga-d15s50k-pbest}{0.002}
1861
+ \herset{ta-her2-tcga-d15s50k-prn}{0.278}
1862
+ \herset{ta-her2-tcga-rn50}{0.567}
1863
+ \herset{ta-her2-tcga-rn50-sd}{0.068}
1864
+ \herset{ta-her2-tcga-rn50-rank}{30}
1865
+ \herset{ta-her2-tcga-rn50-pbest}{0.001}
1866
+ \herset{ta-her2-tcga-d15final}{0.560}
1867
+ \herset{ta-her2-tcga-d15final-sd}{0.097}
1868
+ \herset{ta-her2-tcga-d15final-rank}{31}
1869
+ \herset{ta-her2-tcga-d15final-pbest}{0.007}
1870
+ \herset{ta-her2-tcga-d15final-prn}{0.577}
1871
+ \herset{ta-her2-tcga-d15rand}{0.558}
1872
+ \herset{ta-her2-tcga-d15rand-sd}{0.051}
1873
+ \herset{ta-her2-tcga-d15rand-rank}{32}
1874
+ \herset{ta-her2-tcga-d15rand-pbest}{0.001}
1875
+ \herset{ta-her2-tcga-d15rand-prn}{0.652}
1876
+ \herset{ta-her2-tcga-s16s5}{0.543}
1877
+ \herset{ta-her2-tcga-s16s5-sd}{0.055}
1878
+ \herset{ta-her2-tcga-s16s5-rank}{33}
1879
+ \herset{ta-her2-tcga-s16s5-pbest}{0.002}
1880
+ \herset{ta-her2-tcga-s16s5-prn}{0.722}
1881
+ \herset{ta-her2-tcga-dinov2s}{0.541}
1882
+ \herset{ta-her2-tcga-dinov2s-sd}{0.081}
1883
+ \herset{ta-her2-tcga-dinov2s-rank}{34}
1884
+ \herset{ta-her2-tcga-dinov2s-pbest}{0.003}
1885
+ \herset{ta-her2-tcga-dinov2s-prn}{0.688}
1886
+ \herset{ta-her2-tcga-rand}{0.485}
1887
+ \herset{ta-her2-tcga-rand-sd}{0.054}
1888
+ \herset{ta-her2-tcga-rand-rank}{35}
1889
+ \herset{ta-her2-tcga-rand-pbest}{0.001}
1890
+ \herset{ta-her2-tcga-rand-prn}{0.995}
1891
+ \herset{ta-her2-tcga-n}{35}
1892
+ \herset{ta-her2-tcga-p-phikon-d18s40k}{0.539}
1893
+ \herset{ta-her2-tcga-d-phikon-d18s40k}{-0.006}
1894
+ \herset{ta-her2-tcga-p-phikon-d16final}{0.539}
1895
+ \herset{ta-her2-tcga-d-phikon-d16final}{-0.001}
1896
+ \herset{ta-her2-tcga-ntop}{11}
1897
+ \herset{ta-her2-tcga-bestrank}{6}
1898
+ \herset{ta-her2-tcga-bestgap}{0.002}
1899
+ \herset{ta-her2-yale-hopt1um}{0.913}
1900
+ \herset{ta-her2-yale-hopt1um-sd}{0.067}
1901
+ \herset{ta-her2-yale-hopt1um-rank}{1}
1902
+ \herset{ta-her2-yale-hopt1um-prn}{0.001}
1903
+ \herset{ta-her2-yale-hoptcard}{0.913}
1904
+ \herset{ta-her2-yale-hoptcard-sd}{0.061}
1905
+ \herset{ta-her2-yale-hoptcard-rank}{2}
1906
+ \herset{ta-her2-yale-hoptcard-pbest}{0.451}
1907
+ \herset{ta-her2-yale-hoptcard-prn}{0.001}
1908
+ \herset{ta-her2-yale-hoptcm}{0.911}
1909
+ \herset{ta-her2-yale-hoptcm-sd}{0.057}
1910
+ \herset{ta-her2-yale-hoptcm-rank}{3}
1911
+ \herset{ta-her2-yale-hoptcm-pbest}{0.161}
1912
+ \herset{ta-her2-yale-hoptcm-prn}{0.001}
1913
+ \herset{ta-her2-yale-hoptaug}{0.907}
1914
+ \herset{ta-her2-yale-hoptaug-sd}{0.058}
1915
+ \herset{ta-her2-yale-hoptaug-rank}{4}
1916
+ \herset{ta-her2-yale-hoptaug-pbest}{0.152}
1917
+ \herset{ta-her2-yale-hoptaug-prn}{0.001}
1918
+ \herset{ta-her2-yale-phikon}{0.901}
1919
+ \herset{ta-her2-yale-phikon-sd}{0.059}
1920
+ \herset{ta-her2-yale-phikon-rank}{5}
1921
+ \herset{ta-her2-yale-phikon-pbest}{0.116}
1922
+ \herset{ta-her2-yale-phikon-prn}{0.001}
1923
+ \herset{ta-her2-yale-midnightcm}{0.878}
1924
+ \herset{ta-her2-yale-midnightcm-sd}{0.064}
1925
+ \herset{ta-her2-yale-midnightcm-rank}{6}
1926
+ \herset{ta-her2-yale-midnightcm-pbest}{0.013}
1927
+ \herset{ta-her2-yale-midnightcm-prn}{0.001}
1928
+ \herset{ta-her2-yale-d16final}{0.870}
1929
+ \herset{ta-her2-yale-d16final-sd}{0.053}
1930
+ \herset{ta-her2-yale-d16final-rank}{7}
1931
+ \herset{ta-her2-yale-d16final-pbest}{0.032}
1932
+ \herset{ta-her2-yale-d16final-prn}{0.001}
1933
+ \herset{ta-her2-yale-d18s40k}{0.856}
1934
+ \herset{ta-her2-yale-d18s40k-sd}{0.052}
1935
+ \herset{ta-her2-yale-d18s40k-rank}{8}
1936
+ \herset{ta-her2-yale-d18s40k-pbest}{0.005}
1937
+ \herset{ta-her2-yale-d18s40k-prn}{0.003}
1938
+ \herset{ta-her2-yale-d14}{0.856}
1939
+ \herset{ta-her2-yale-d14-sd}{0.046}
1940
+ \herset{ta-her2-yale-d14-rank}{9}
1941
+ \herset{ta-her2-yale-d14-pbest}{0.002}
1942
+ \herset{ta-her2-yale-d14-prn}{0.001}
1943
+ \herset{ta-her2-yale-midnight}{0.856}
1944
+ \herset{ta-her2-yale-midnight-sd}{0.043}
1945
+ \herset{ta-her2-yale-midnight-rank}{10}
1946
+ \herset{ta-her2-yale-midnight-pbest}{0.007}
1947
+ \herset{ta-her2-yale-midnight-prn}{0.001}
1948
+ \herset{ta-her2-yale-hibou}{0.853}
1949
+ \herset{ta-her2-yale-hibou-sd}{0.062}
1950
+ \herset{ta-her2-yale-hibou-rank}{11}
1951
+ \herset{ta-her2-yale-hibou-pbest}{0.001}
1952
+ \herset{ta-her2-yale-hibou-prn}{0.002}
1953
+ \herset{ta-her2-yale-d18s50k}{0.851}
1954
+ \herset{ta-her2-yale-d18s50k-sd}{0.046}
1955
+ \herset{ta-her2-yale-d18s50k-rank}{12}
1956
+ \herset{ta-her2-yale-d18s50k-pbest}{0.007}
1957
+ \herset{ta-her2-yale-d18s50k-prn}{0.003}
1958
+ \herset{ta-her2-yale-b16s35}{0.847}
1959
+ \herset{ta-her2-yale-b16s35-sd}{0.047}
1960
+ \herset{ta-her2-yale-b16s35-rank}{13}
1961
+ \herset{ta-her2-yale-b16s35-pbest}{0.002}
1962
+ \herset{ta-her2-yale-b16s35-prn}{0.001}
1963
+ \herset{ta-her2-yale-d16s50k}{0.846}
1964
+ \herset{ta-her2-yale-d16s50k-sd}{0.052}
1965
+ \herset{ta-her2-yale-d16s50k-rank}{14}
1966
+ \herset{ta-her2-yale-d16s50k-pbest}{0.004}
1967
+ \herset{ta-her2-yale-d16s50k-prn}{0.001}
1968
+ \herset{ta-her2-yale-s16s55}{0.845}
1969
+ \herset{ta-her2-yale-s16s55-sd}{0.057}
1970
+ \herset{ta-her2-yale-s16s55-rank}{15}
1971
+ \herset{ta-her2-yale-s16s55-pbest}{0.005}
1972
+ \herset{ta-her2-yale-s16s55-prn}{0.001}
1973
+ \herset{ta-her2-yale-midnight1um}{0.840}
1974
+ \herset{ta-her2-yale-midnight1um-sd}{0.063}
1975
+ \herset{ta-her2-yale-midnight1um-rank}{16}
1976
+ \herset{ta-her2-yale-midnight1um-pbest}{0.002}
1977
+ \herset{ta-her2-yale-midnight1um-prn}{0.002}
1978
+ \herset{ta-her2-yale-b16s40}{0.840}
1979
+ \herset{ta-her2-yale-b16s40-sd}{0.060}
1980
+ \herset{ta-her2-yale-b16s40-rank}{17}
1981
+ \herset{ta-her2-yale-b16s40-pbest}{0.003}
1982
+ \herset{ta-her2-yale-b16s40-prn}{0.001}
1983
+ \herset{ta-her2-yale-d18s45k}{0.839}
1984
+ \herset{ta-her2-yale-d18s45k-sd}{0.049}
1985
+ \herset{ta-her2-yale-d18s45k-rank}{18}
1986
+ \herset{ta-her2-yale-d18s45k-pbest}{0.002}
1987
+ \herset{ta-her2-yale-d18s45k-prn}{0.005}
1988
+ \herset{ta-her2-yale-d13}{0.838}
1989
+ \herset{ta-her2-yale-d13-sd}{0.066}
1990
+ \herset{ta-her2-yale-d13-rank}{19}
1991
+ \herset{ta-her2-yale-d13-pbest}{0.005}
1992
+ \herset{ta-her2-yale-d13-prn}{0.002}
1993
+ \herset{ta-her2-yale-s16s35}{0.831}
1994
+ \herset{ta-her2-yale-s16s35-sd}{0.058}
1995
+ \herset{ta-her2-yale-s16s35-rank}{20}
1996
+ \herset{ta-her2-yale-s16s35-pbest}{0.001}
1997
+ \herset{ta-her2-yale-s16s35-prn}{0.001}
1998
+ \herset{ta-her2-yale-s16s50}{0.831}
1999
+ \herset{ta-her2-yale-s16s50-sd}{0.071}
2000
+ \herset{ta-her2-yale-s16s50-rank}{21}
2001
+ \herset{ta-her2-yale-s16s50-pbest}{0.003}
2002
+ \herset{ta-her2-yale-s16s50-prn}{0.001}
2003
+ \herset{ta-her2-yale-s16s40}{0.830}
2004
+ \herset{ta-her2-yale-s16s40-sd}{0.070}
2005
+ \herset{ta-her2-yale-s16s40-rank}{22}
2006
+ \herset{ta-her2-yale-s16s40-pbest}{0.010}
2007
+ \herset{ta-her2-yale-s16s40-prn}{0.010}
2008
+ \herset{ta-her2-yale-d16rand}{0.828}
2009
+ \herset{ta-her2-yale-d16rand-sd}{0.077}
2010
+ \herset{ta-her2-yale-d16rand-rank}{23}
2011
+ \herset{ta-her2-yale-d16rand-pbest}{0.003}
2012
+ \herset{ta-her2-yale-d16rand-prn}{0.002}
2013
+ \herset{ta-her2-yale-s16s60}{0.827}
2014
+ \herset{ta-her2-yale-s16s60-sd}{0.047}
2015
+ \herset{ta-her2-yale-s16s60-rank}{24}
2016
+ \herset{ta-her2-yale-s16s60-pbest}{0.003}
2017
+ \herset{ta-her2-yale-s16s60-prn}{0.001}
2018
+ \herset{ta-her2-yale-s16final}{0.827}
2019
+ \herset{ta-her2-yale-s16final-sd}{0.048}
2020
+ \herset{ta-her2-yale-s16final-rank}{25}
2021
+ \herset{ta-her2-yale-s16final-pbest}{0.001}
2022
+ \herset{ta-her2-yale-s16final-prn}{0.001}
2023
+ \herset{ta-her2-yale-b16s45}{0.820}
2024
+ \herset{ta-her2-yale-b16s45-sd}{0.047}
2025
+ \herset{ta-her2-yale-b16s45-rank}{26}
2026
+ \herset{ta-her2-yale-b16s45-pbest}{0.001}
2027
+ \herset{ta-her2-yale-b16s45-prn}{0.001}
2028
+ \herset{ta-her2-yale-s16s45}{0.817}
2029
+ \herset{ta-her2-yale-s16s45-sd}{0.058}
2030
+ \herset{ta-her2-yale-s16s45-rank}{27}
2031
+ \herset{ta-her2-yale-s16s45-pbest}{0.001}
2032
+ \herset{ta-her2-yale-s16s45-prn}{0.001}
2033
+ \herset{ta-her2-yale-b16s20}{0.813}
2034
+ \herset{ta-her2-yale-b16s20-sd}{0.051}
2035
+ \herset{ta-her2-yale-b16s20-rank}{28}
2036
+ \herset{ta-her2-yale-b16s20-pbest}{0.001}
2037
+ \herset{ta-her2-yale-b16s20-prn}{0.002}
2038
+ \herset{ta-her2-yale-d15final}{0.809}
2039
+ \herset{ta-her2-yale-d15final-sd}{0.059}
2040
+ \herset{ta-her2-yale-d15final-rank}{29}
2041
+ \herset{ta-her2-yale-d15final-pbest}{0.002}
2042
+ \herset{ta-her2-yale-d15final-prn}{0.002}
2043
+ \herset{ta-her2-yale-d15s50k}{0.808}
2044
+ \herset{ta-her2-yale-d15s50k-sd}{0.044}
2045
+ \herset{ta-her2-yale-d15s50k-rank}{30}
2046
+ \herset{ta-her2-yale-d15s50k-pbest}{0.002}
2047
+ \herset{ta-her2-yale-d15s50k-prn}{0.005}
2048
+ \herset{ta-her2-yale-d15rand}{0.807}
2049
+ \herset{ta-her2-yale-d15rand-sd}{0.057}
2050
+ \herset{ta-her2-yale-d15rand-rank}{31}
2051
+ \herset{ta-her2-yale-d15rand-pbest}{0.001}
2052
+ \herset{ta-her2-yale-d15rand-prn}{0.010}
2053
+ \herset{ta-her2-yale-s16s65}{0.802}
2054
+ \herset{ta-her2-yale-s16s65-sd}{0.045}
2055
+ \herset{ta-her2-yale-s16s65-rank}{32}
2056
+ \herset{ta-her2-yale-s16s65-pbest}{0.002}
2057
+ \herset{ta-her2-yale-s16s65-prn}{0.001}
2058
+ \herset{ta-her2-yale-s16s20}{0.799}
2059
+ \herset{ta-her2-yale-s16s20-sd}{0.073}
2060
+ \herset{ta-her2-yale-s16s20-rank}{33}
2061
+ \herset{ta-her2-yale-s16s20-pbest}{0.001}
2062
+ \herset{ta-her2-yale-s16s20-prn}{0.004}
2063
+ \herset{ta-her2-yale-dinov2s}{0.794}
2064
+ \herset{ta-her2-yale-dinov2s-sd}{0.057}
2065
+ \herset{ta-her2-yale-dinov2s-rank}{34}
2066
+ \herset{ta-her2-yale-dinov2s-pbest}{0.001}
2067
+ \herset{ta-her2-yale-dinov2s-prn}{0.024}
2068
+ \herset{ta-her2-yale-s16s5}{0.786}
2069
+ \herset{ta-her2-yale-s16s5-sd}{0.083}
2070
+ \herset{ta-her2-yale-s16s5-rank}{35}
2071
+ \herset{ta-her2-yale-s16s5-pbest}{0.001}
2072
+ \herset{ta-her2-yale-s16s5-prn}{0.032}
2073
+ \herset{ta-her2-yale-b16s10}{0.756}
2074
+ \herset{ta-her2-yale-b16s10-sd}{0.054}
2075
+ \herset{ta-her2-yale-b16s10-rank}{36}
2076
+ \herset{ta-her2-yale-b16s10-pbest}{0.001}
2077
+ \herset{ta-her2-yale-b16s10-prn}{0.097}
2078
+ \herset{ta-her2-yale-rn50}{0.730}
2079
+ \herset{ta-her2-yale-rn50-sd}{0.073}
2080
+ \herset{ta-her2-yale-rn50-rank}{37}
2081
+ \herset{ta-her2-yale-rn50-pbest}{0.001}
2082
+ \herset{ta-her2-yale-rand}{0.661}
2083
+ \herset{ta-her2-yale-rand-sd}{0.065}
2084
+ \herset{ta-her2-yale-rand-rank}{38}
2085
+ \herset{ta-her2-yale-rand-pbest}{0.001}
2086
+ \herset{ta-her2-yale-rand-prn}{0.995}
2087
+ \herset{ta-her2-yale-n}{38}
2088
+ \herset{ta-her2-yale-p-phikon-d18s40k}{0.014}
2089
+ \herset{ta-her2-yale-d-phikon-d18s40k}{+0.045}
2090
+ \herset{ta-her2-yale-p-phikon-d16final}{0.080}
2091
+ \herset{ta-her2-yale-d-phikon-d16final}{+0.031}
2092
+ \herset{ta-her2-yale-ntop}{5}
2093
+ \herset{ta-her2-yale-bestrank}{7}
2094
+ \herset{ta-her2-yale-bestgap}{0.043}
2095
+ \herset{agree-yale}{0.93}
2096
+ \herset{agree-yale-n}{36}
2097
+ \herset{agree-tcga}{0.87}
2098
+ \herset{agree-tcga-n}{35}
2099
+ \herset{seedsd-median}{0.012}
2100
+ \herset{seedsd-max}{0.066}
2101
+ \herset{seedsd-n}{152}
2102
+ \herset{ta-her2-tcga-check}{matches}
2103
+ \herset{ta-her2-yale-check}{matches}
2104
+ \herset{ov-cohort-slides}{490}
2105
+ \herset{ov-cohort-cases}{490}
2106
+ \herset{ov-cohort-positive}{156}
2107
+ \herset{ov-corpus-selected-slides}{9,752}
2108
+ \herset{ov-corpus-selected-brca}{1,062}
2109
+ \herset{ov-corpus-programmes}{TCGA}
2110
+ \herset{ov-overlap-slides}{490}
2111
+ \herset{ov-overlap-cases}{490}
2112
+ \herset{ov-overlap-positive-slides}{156}
data/paper/book-data/her2_matrix.dat ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ key group probe yy yy_sd tt tt_sd ty ty_sd yt yt_sd yy_mf yy_mf_sd tt_mf tt_mf_sd ty_mf ty_mf_sd yt_mf yt_mf_sd
2
+ vits16-random-init ctl 0.0962 0.5900 0.0040 0.5080 0.0124 0.4375 0.0317 0.4849 0.0020 0.6021 0.0104 0.5166 0.0137 0.4466 0.0333 0.4892 0.0020
3
+ dinov2-vits14 ctl 0.3104 0.7192 0.0203 0.5011 0.0226 0.5889 0.0203 0.5764 0.0115 0.7333 0.0085 0.5249 0.0178 0.5615 0.0139 0.5629 0.0065
4
+ resnet50-imagenet ctl nan 0.7009 0.0427 0.5517 0.0279 0.6296 0.0149 0.5606 0.0069 0.7204 0.0603 0.5541 0.0277 0.6048 0.0082 0.5400 0.0031
5
+ ssl-vits16-step5k s16 0.1954 0.7264 0.0064 0.5697 0.0129 0.6764 0.0184 0.5228 0.0041 0.7500 0.0056 0.5762 0.0147 0.6074 0.0217 0.5122 0.0058
6
+ ssl-vits16-step20k s16 0.2883 0.7382 0.0126 0.5675 0.0106 0.6174 0.0430 0.5451 0.0010 0.7838 0.0231 0.5838 0.0086 0.5928 0.0179 0.5393 0.0016
7
+ ssl-vits16-step35k s16 0.3337 0.8039 0.0106 0.5992 0.0082 0.5613 0.0149 0.5306 0.0038 0.8191 0.0050 0.6349 0.0055 0.5750 0.0144 0.5265 0.0048
8
+ ssl-vits16-step40k s16 0.3363 0.7919 0.0193 0.6199 0.0090 0.5651 0.0174 0.5144 0.0034 0.8122 0.0083 0.6318 0.0188 0.5590 0.0152 0.5137 0.0028
9
+ ssl-vits16-step45k s16 0.3368 0.7601 0.0245 0.5887 0.0192 0.5873 0.0660 0.5253 0.0061 0.7785 0.0237 0.5968 0.0295 0.5824 0.0382 0.5262 0.0033
10
+ ssl-vits16-step50k s16 0.3379 0.7808 0.0174 0.6085 0.0042 0.5499 0.0167 0.5281 0.0060 0.8165 0.0120 0.6248 0.0064 0.5506 0.0041 0.5204 0.0063
11
+ ssl-vits16-step55k s16 0.3422 0.7880 0.0285 0.5888 0.0031 0.6004 0.0520 0.5322 0.0064 0.8096 0.0256 0.6164 0.0160 0.5806 0.0272 0.5236 0.0040
12
+ ssl-vits16-step60k s16 0.3412 0.7775 0.0090 0.5958 0.0062 0.5922 0.0314 0.5318 0.0034 0.8186 0.0078 0.6057 0.0076 0.5742 0.0079 0.5262 0.0047
13
+ ssl-vits16-step65k s16 0.3448 0.7588 0.0154 0.6211 0.0165 0.5530 0.0541 0.5177 0.0018 0.8045 0.0095 0.6338 0.0107 0.5392 0.0256 0.5188 0.0055
14
+ ssl-vits16-final s16 0.3415 0.7675 0.0267 0.5891 0.0128 0.5841 0.0385 0.5205 0.0029 0.8204 0.0206 0.6085 0.0177 0.5872 0.0372 0.5155 0.0030
15
+ ssl-vitb16-step10k b16 0.2753 0.7575 0.0358 0.5877 0.0045 0.5724 0.0202 0.5307 0.0105 0.7751 0.0165 0.6038 0.0033 0.5575 0.0028 0.5275 0.0085
16
+ ssl-vitb16-step35k b16 0.3636 0.8290 0.0099 0.5819 0.0184 0.6380 0.0233 0.5455 0.0017 0.8518 0.0021 0.6152 0.0111 0.5975 0.0230 0.5364 0.0029
17
+ ssl-vitb16-step40k b16 0.3834 0.7934 0.0135 0.6074 0.0161 0.6651 0.0377 0.5472 0.0057 0.8103 0.0140 0.6306 0.0085 0.6187 0.0115 0.5319 0.0027
18
+ distill-midnight-20k dst 0.4872 0.7714 0.0195 0.5899 0.0170 0.7010 0.0206 0.5454 0.0081 0.8063 0.0047 0.5863 0.0236 0.6666 0.0171 0.5403 0.0053
19
+ distill-hoptimus-20k dst 0.4891 0.8064 0.0183 0.6688 0.0101 0.7157 0.0151 0.5733 0.0040 0.8438 0.0134 0.6764 0.0125 0.6989 0.0201 0.5672 0.0056
20
+ distill-midnight-5k-from-random dst 0.2887 0.7616 0.0241 0.5474 0.0242 0.6205 0.0347 0.5288 0.0026 0.7686 0.0230 0.5606 0.0207 0.5987 0.0349 0.5241 0.0050
21
+ distill-midnight-5k-from-vits16-step50k dst 0.4502 0.7718 0.0161 0.5688 0.0093 0.7244 0.0175 0.5576 0.0113 0.8077 0.0152 0.5826 0.0130 0.6784 0.0132 0.5555 0.0049
22
+ distill-midnight-5k-from-vits16-final dst 0.4605 0.7923 0.0214 0.5878 0.0072 0.6512 0.0293 0.5526 0.0017 0.8221 0.0128 0.6054 0.0199 0.6192 0.0122 0.5426 0.0035
23
+ distill-hoptimus-5k-from-random dst 0.3291 0.7922 0.0088 0.5922 0.0143 0.7387 0.0281 0.5632 0.0016 0.8157 0.0167 0.6197 0.0025 0.6986 0.0170 0.5618 0.0011
24
+ distill-hoptimus-5k-from-vits16-step50k dst 0.4459 0.8143 0.0083 0.6361 0.0038 0.7393 0.0173 0.6215 0.0038 0.8295 0.0044 0.6721 0.0082 0.7225 0.0131 0.5962 0.0058
25
+ distill-hoptimus-5k-from-vits16-final dst 0.4514 0.8196 0.0197 0.6228 0.0229 0.7443 0.0219 0.5930 0.0059 0.8425 0.0088 0.6577 0.0155 0.7283 0.0126 0.5774 0.0025
26
+ distill-hoptimus-vitb16-5k-from-vitb16-step40k dstb 0.4714 0.8177 0.0098 0.6332 0.0157 0.7757 0.0098 0.6406 0.0080 0.8471 0.0013 0.6621 0.0065 0.7585 0.0118 0.6224 0.0025
27
+ distill-hoptimus-vitb16-5k-from-vitb16-step45k dstb 0.4797 0.7765 0.0094 0.6329 0.0143 0.7623 0.0040 0.6215 0.0069 0.8289 0.0128 0.6675 0.0138 0.7474 0.0091 0.6038 0.0048
28
+ distill-hoptimus-vitb16-5k-from-vitb16-step50k dstb 0.4899 0.8032 0.0397 0.6148 0.0022 0.7547 0.0075 0.6136 0.0012 0.8414 0.0124 0.6414 0.0020 0.7293 0.0107 0.6005 0.0038
29
+ hibou-b ref nan 0.7794 0.0119 0.6442 0.0161 0.7172 0.0299 0.6309 0.0105 0.8167 0.0151 0.6643 0.0093 0.6791 0.0243 0.6057 0.0049
30
+ phikon ref 0.5507 0.8756 0.0047 0.6690 0.0085 0.8128 0.0191 0.6606 0.0003 0.8902 0.0064 0.6872 0.0065 0.7682 0.0168 0.6484 0.0030
31
+ virchow2 ref nan 0.8673 0.0086 0.6336 0.0146 0.7425 0.0349 0.6541 0.0058 0.8889 0.0095 0.6652 0.0192 0.7082 0.0240 0.6356 0.0092
32
+ midnight12k ref 0.6904 0.8064 0.0091 0.5970 0.0028 0.7163 0.0086 0.6240 0.0039 0.8340 0.0028 0.6111 0.0049 0.6954 0.0027 0.6059 0.0020
33
+ midnight12k-cls-mean ref 0.7050 0.8114 0.0112 0.6105 0.0084 0.7337 0.0209 0.6376 0.0039 0.8533 0.0071 0.6324 0.0042 0.6998 0.0115 0.6271 0.0043
34
+ midnight12k-1.0um ref nan 0.8013 0.0060 0.5858 0.0127 0.7243 0.0269 0.6087 0.0054 0.8253 0.0222 0.5984 0.0129 0.6807 0.0189 0.6007 0.0034
35
+ hoptimus0-imagenetnorm ref nan 0.8978 0.0104 0.6685 0.0232 0.7977 0.0172 0.6562 0.0013 0.9119 0.0064 0.6828 0.0155 0.7465 0.0191 0.6420 0.0020
36
+ hoptimus0-imagenetnorm-repeat ref nan 0.8954 0.0143 0.6683 0.0145 0.7871 0.0310 0.6562 0.0052 0.9124 0.0064 0.6784 0.0145 0.7509 0.0163 0.6425 0.0028
37
+ hoptimus0-cardnorm ref 0.5811 0.8868 0.0072 0.6755 0.0162 0.8100 0.0116 0.6531 0.0078 0.9056 0.0065 0.6957 0.0132 0.7642 0.0102 0.6419 0.0071
38
+ hoptimus0-cls-mean ref 0.5920 0.8925 0.0157 0.6723 0.0179 0.8028 0.0253 0.6630 0.0057 0.9151 0.0018 0.6882 0.0111 0.7640 0.0115 0.6488 0.0050
39
+ hoptimus0-1.0um ref nan 0.9088 0.0066 0.6591 0.0153 0.8033 0.0109 0.6419 0.0071 0.9247 0.0076 0.6774 0.0127 0.7640 0.0200 0.6298 0.0042
data/paper/book-data/her2_traj_vitb16.dat ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ step probe yy yy_sd tt tt_sd ty ty_sd yt yt_sd
2
+ 10000 0.2753 0.7575 0.0358 0.5877 0.0045 0.5724 0.0202 0.5307 0.0105
3
+ 35000 0.3636 0.8290 0.0099 0.5819 0.0184 0.6380 0.0233 0.5455 0.0017
4
+ 40000 0.3834 0.7934 0.0135 0.6074 0.0161 0.6651 0.0377 0.5472 0.0057
data/paper/book-data/her2_traj_vits16.dat ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ step probe yy yy_sd tt tt_sd ty ty_sd yt yt_sd
2
+ 5000 0.1954 0.7264 0.0064 0.5697 0.0129 0.6764 0.0184 0.5228 0.0041
3
+ 20000 0.2883 0.7382 0.0126 0.5675 0.0106 0.6174 0.0430 0.5451 0.0010
4
+ 35000 0.3337 0.8039 0.0106 0.5992 0.0082 0.5613 0.0149 0.5306 0.0038
5
+ 40000 0.3363 0.7919 0.0193 0.6199 0.0090 0.5651 0.0174 0.5144 0.0034
6
+ 45000 0.3368 0.7601 0.0245 0.5887 0.0192 0.5873 0.0660 0.5253 0.0061
7
+ 50000 0.3379 0.7808 0.0174 0.6085 0.0042 0.5499 0.0167 0.5281 0.0060
8
+ 55000 0.3422 0.7880 0.0285 0.5888 0.0031 0.6004 0.0520 0.5322 0.0064
9
+ 60000 0.3412 0.7775 0.0090 0.5958 0.0062 0.5922 0.0314 0.5318 0.0034
10
+ 65000 0.3448 0.7588 0.0154 0.6211 0.0165 0.5530 0.0541 0.5177 0.0018
11
+ 93338 0.3415 0.7675 0.0267 0.5891 0.0128 0.5841 0.0385 0.5205 0.0029
data/paper/book-data/her2_vs_trackA.dat ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ key group yy ta_yale tt ta_tcga
2
+ dinov2-vits14 ctl 0.7192 0.7939 0.5011 0.5410
3
+ distill-hoptimus-20k dst 0.8064 0.8561 0.6688 0.6532
4
+ distill-hoptimus-5k-from-random dst 0.7922 0.8282 0.5922 0.5905
5
+ distill-hoptimus-5k-from-vits16-final best 0.8196 0.8697 0.6228 0.6578
6
+ distill-hoptimus-5k-from-vits16-step50k dst 0.8143 0.8455 0.6361 0.6512
7
+ distill-hoptimus-vitb16-5k-from-vitb16-step40k dstb 0.8177 0.8563 0.6332 0.6627
8
+ distill-hoptimus-vitb16-5k-from-vitb16-step45k dstb 0.7765 0.8395 0.6329 0.6452
9
+ distill-hoptimus-vitb16-5k-from-vitb16-step50k dstb 0.8032 0.8513 0.6148 nan
10
+ distill-midnight-20k dst 0.7714 0.8384 0.5899 0.6159
11
+ distill-midnight-5k-from-random dst 0.7616 0.8068 0.5474 0.5578
12
+ distill-midnight-5k-from-vits16-final dst 0.7923 0.8092 0.5878 0.5601
13
+ distill-midnight-5k-from-vits16-step50k dst 0.7718 0.8079 0.5688 0.5719
14
+ hibou-b ref 0.7794 0.8534 0.6442 0.6050
15
+ hoptimus0-1.0um ref 0.9088 0.9134 0.6591 0.6655
16
+ hoptimus0-cardnorm ref 0.8868 0.9129 0.6755 0.6597
17
+ hoptimus0-cls-mean ref 0.8925 0.9105 0.6723 0.6694
18
+ hoptimus0-imagenetnorm ref 0.8978 0.9068 0.6685 0.6588
19
+ midnight12k ref 0.8064 0.8555 0.5970 0.6063
20
+ midnight12k-1.0um ref 0.8013 0.8403 0.5858 0.6033
21
+ midnight12k-cls-mean ref 0.8114 0.8776 0.6105 0.6299
22
+ phikon ref 0.8756 0.9011 0.6690 0.6563
23
+ resnet50-imagenet ctl 0.7009 0.7303 0.5517 0.5670
24
+ ssl-vitb16-step10k b16 0.7575 0.7561 0.5877 0.5915
25
+ ssl-vitb16-step35k b16 0.8290 0.8466 0.5819 0.5895
26
+ ssl-vitb16-step40k b16 0.7934 0.8400 0.6074 0.6214
27
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230
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231
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232
+ \mset{pd-phikon-dbs40-yt-p}{0.001}
233
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234
+ \mset{pdn-hopt-dbs40-yy}{0.0829}
235
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236
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237
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238
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239
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240
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241
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242
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243
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244
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245
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246
+ \mset{pdn-hopt-dbs40-yt}{0.0090}
247
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248
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249
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250
+ \mset{pdn-dbs40-b40-yy}{0.0196}
251
+ \mset{pd-dbs40-b40-yy-k}{8/10}
252
+ \mset{pd-dbs40-b40-yy-p}{0.024}
253
+ \mset{pd-dbs40-b40-tt}{+0.037}
254
+ \mset{pdn-dbs40-b40-tt}{0.0374}
255
+ \mset{pd-dbs40-b40-tt-k}{10/10}
256
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257
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258
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259
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260
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261
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262
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263
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264
+ \mset{pd-dbs40-b40-yt-p}{0.001}
265
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266
+ \mset{pdn-dbs40-dbm40-yy}{-0.0016}
267
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268
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269
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270
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271
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272
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273
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274
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275
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276
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277
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278
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279
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280
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281
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282
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283
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284
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285
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286
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287
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288
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289
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290
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291
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292
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293
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294
+ \mset{pdn-dsx23-dsfinal-yt}{0.0012}
295
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296
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297
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298
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299
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300
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301
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302
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303
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304
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305
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306
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307
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308
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309
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310
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311
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312
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313
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314
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315
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316
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317
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318
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319
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320
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321
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322
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323
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324
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325
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326
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327
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328
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329
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330
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331
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332
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333
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334
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335
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336
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337
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338
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339
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340
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341
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342
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343
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344
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345
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346
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347
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348
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349
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350
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351
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352
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353
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354
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355
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356
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357
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358
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359
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360
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361
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362
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363
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364
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365
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366
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367
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368
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369
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370
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371
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372
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373
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374
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375
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376
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377
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378
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379
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380
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381
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382
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383
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384
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385
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386
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387
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388
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389
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390
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391
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392
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393
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394
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395
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396
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397
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398
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399
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400
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401
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402
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403
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404
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405
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406
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407
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408
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409
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410
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411
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412
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413
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414
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415
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416
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417
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418
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419
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420
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421
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422
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423
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424
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425
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426
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427
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428
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429
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430
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431
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432
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433
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434
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435
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436
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437
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438
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439
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440
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441
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442
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443
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444
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445
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446
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447
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448
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449
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450
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451
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452
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453
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454
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455
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456
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457
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458
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459
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460
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461
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462
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463
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464
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465
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466
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467
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468
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469
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470
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471
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472
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473
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474
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475
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476
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477
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478
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479
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480
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481
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482
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483
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484
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485
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486
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487
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488
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489
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490
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491
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492
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493
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494
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495
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496
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497
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498
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499
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500
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501
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502
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503
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504
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505
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506
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507
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508
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509
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510
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511
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512
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513
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514
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515
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516
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517
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519
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520
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521
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522
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523
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524
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526
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527
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528
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529
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530
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531
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532
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533
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534
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535
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536
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537
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538
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539
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540
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541
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542
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543
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544
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547
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548
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550
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551
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552
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553
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555
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556
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557
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558
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559
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560
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561
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562
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563
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565
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567
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568
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570
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571
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572
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573
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574
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575
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576
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577
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578
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579
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580
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585
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586
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587
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588
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589
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590
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591
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592
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593
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594
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595
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596
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597
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598
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600
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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634
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635
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636
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637
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638
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639
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640
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641
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642
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643
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
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665
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666
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667
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668
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669
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670
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671
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672
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673
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674
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675
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676
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677
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678
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679
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
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729
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730
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731
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732
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733
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734
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735
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736
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737
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738
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739
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740
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741
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742
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743
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744
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745
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746
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747
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748
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749
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750
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751
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752
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753
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754
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755
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756
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757
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758
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759
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760
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761
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762
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763
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764
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765
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766
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767
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768
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769
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770
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771
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772
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773
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774
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775
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776
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777
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778
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779
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780
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781
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782
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783
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784
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785
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786
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787
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788
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789
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790
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791
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792
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793
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794
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795
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796
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797
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798
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799
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800
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801
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802
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803
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804
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805
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806
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807
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808
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809
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810
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811
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812
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813
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814
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815
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816
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817
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818
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819
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820
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821
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822
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823
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824
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825
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826
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827
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828
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829
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830
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831
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832
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833
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834
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835
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836
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837
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838
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839
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840
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841
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842
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843
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844
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845
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846
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847
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848
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849
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850
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851
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852
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853
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854
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855
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856
+ \mset{k2td-phikon-tt-p}{0.080}
857
+ \mset{k32d-phikon-tt}{$-$0.001}
858
+ \mset{k32d-phikon-tt-k}{4/10}
859
+ \mset{k32d-phikon-tt-p}{0.500}
860
+ \mset{k2t-phikon-ty}{0.799}
861
+ \mset{k2td-phikon-ty}{$-$0.012}
862
+ \mset{k2td-phikon-ty-k}{2/10}
863
+ \mset{k2td-phikon-ty-p}{0.032}
864
+ \mset{k32d-phikon-ty}{$-$0.024}
865
+ \mset{k32d-phikon-ty-k}{0/10}
866
+ \mset{k32d-phikon-ty-p}{0.002}
867
+ \mset{k2t-phikon-yt}{0.662}
868
+ \mset{k2td-phikon-yt}{+0.000}
869
+ \mset{k2td-phikon-yt-k}{5/10}
870
+ \mset{k2td-phikon-yt-p}{0.385}
871
+ \mset{k32d-phikon-yt}{$-$0.004}
872
+ \mset{k32d-phikon-yt-k}{1/10}
873
+ \mset{k32d-phikon-yt-p}{0.014}
874
+ \mset{k2gap-yy}{+0.026}
875
+ \mset{k2gap-yy-k}{9/10}
876
+ \mset{k2gap-yy-p}{0.007}
877
+ \mset{k2gap-tt}{$-$0.028}
878
+ \mset{k2gap-tt-k}{0/10}
879
+ \mset{k2gap-tt-p}{0.001}
880
+ \mset{k2gap-ty}{+0.046}
881
+ \mset{k2gap-ty-k}{10/10}
882
+ \mset{k2gap-ty-p}{0.001}
883
+ \mset{k2gap-yt}{+0.031}
884
+ \mset{k2gap-yt-k}{10/10}
885
+ \mset{k2gap-yt-p}{0.001}
886
+ \mset{k3gap-base-yy}{+0.037}
887
+ \mset{k3gap-base-yy-k}{10/10}
888
+ \mset{k3gap-base-yy-p}{0.001}
889
+ \mset{k3gap-k3-yy}{+0.041}
890
+ \mset{k3gap-k3-yy-k}{9/10}
891
+ \mset{k3gap-k3-yy-p}{0.002}
892
+ \mset{k3gap-base-tt}{$-$0.018}
893
+ \mset{k3gap-base-tt-k}{1/10}
894
+ \mset{k3gap-base-tt-p}{0.002}
895
+ \mset{k3gap-k3-tt}{$-$0.030}
896
+ \mset{k3gap-k3-tt-k}{1/10}
897
+ \mset{k3gap-k3-tt-p}{0.002}
898
+ \mset{k3gap-base-ty}{+0.054}
899
+ \mset{k3gap-base-ty-k}{10/10}
900
+ \mset{k3gap-base-ty-p}{0.001}
901
+ \mset{k3gap-k3-ty}{+0.009}
902
+ \mset{k3gap-k3-ty-k}{8/10}
903
+ \mset{k3gap-k3-ty-p}{0.042}
904
+ \mset{k3gap-base-yt}{+0.030}
905
+ \mset{k3gap-base-yt-k}{10/10}
906
+ \mset{k3gap-base-yt-p}{0.001}
907
+ \mset{k3gap-k3-yt}{+0.022}
908
+ \mset{k3gap-k3-yt-k}{10/10}
909
+ \mset{k3gap-k3-yt-p}{0.001}
910
+ \mset{mj-m5b-25-yy}{0.837}
911
+ \mset{mjd-m5b-25-yy}{+0.002}
912
+ \mset{mjd-m5b-25-yy-k}{7/10}
913
+ \mset{mjd-m5b-25-yy-p}{0.461}
914
+ \mset{mj-m5b-25-tt}{0.686}
915
+ \mset{mjd-m5b-25-tt}{$-$0.011}
916
+ \mset{mjd-m5b-25-tt-k}{3/10}
917
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918
+ \mset{mj-m5b-25-ty}{0.774}
919
+ \mset{mjd-m5b-25-ty}{+0.018}
920
+ \mset{mjd-m5b-25-ty-k}{8/10}
921
+ \mset{mjd-m5b-25-ty-p}{0.007}
922
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923
+ \mset{mjd-m5b-25-yt}{$-$0.009}
924
+ \mset{mjd-m5b-25-yt-k}{0/10}
925
+ \mset{mjd-m5b-25-yt-p}{0.001}
926
+ \mset{mj-m5b-50-yy}{0.832}
927
+ \mset{mjd-m5b-50-yy}{$-$0.003}
928
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929
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930
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931
+ \mset{mjd-m5b-50-tt}{+0.002}
932
+ \mset{mjd-m5b-50-tt-k}{6/10}
933
+ \mset{mjd-m5b-50-tt-p}{0.385}
934
+ \mset{mj-m5b-50-ty}{0.783}
935
+ \mset{mjd-m5b-50-ty}{+0.026}
936
+ \mset{mjd-m5b-50-ty-k}{9/10}
937
+ \mset{mjd-m5b-50-ty-p}{0.002}
938
+ \mset{mj-m5b-50-yt}{0.639}
939
+ \mset{mjd-m5b-50-yt}{+0.007}
940
+ \mset{mjd-m5b-50-yt-k}{10/10}
941
+ \mset{mjd-m5b-50-yt-p}{0.001}
942
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943
+ \mset{mjd-m5b-75-yy}{+0.009}
944
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945
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946
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947
+ \mset{mjd-m5b-75-tt}{$-$0.001}
948
+ \mset{mjd-m5b-75-tt-k}{5/10}
949
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950
+ \mset{mj-m5b-75-ty}{0.741}
951
+ \mset{mjd-m5b-75-ty}{$-$0.016}
952
+ \mset{mjd-m5b-75-ty-k}{0/10}
953
+ \mset{mjd-m5b-75-ty-p}{0.001}
954
+ \mset{mj-m5b-75-yt}{0.640}
955
+ \mset{mjd-m5b-75-yt}{+0.007}
956
+ \mset{mjd-m5b-75-yt-k}{10/10}
957
+ \mset{mjd-m5b-75-yt-p}{0.001}
958
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959
+ \mset{mj-m5b-100-tt}{0.697}
960
+ \mset{mj-m5b-100-ty}{0.757}
961
+ \mset{mj-m5b-100-yt}{0.632}
962
+ \mset{mj-m5s-25-yy}{0.858}
963
+ \mset{mjd-m5s-25-yy}{+0.017}
964
+ \mset{mjd-m5s-25-yy-k}{7/10}
965
+ \mset{mjd-m5s-25-yy-p}{0.065}
966
+ \mset{mj-m5s-25-tt}{0.705}
967
+ \mset{mjd-m5s-25-tt}{+0.017}
968
+ \mset{mjd-m5s-25-tt-k}{8/10}
969
+ \mset{mjd-m5s-25-tt-p}{0.019}
970
+ \mset{mj-m5s-25-ty}{0.762}
971
+ \mset{mjd-m5s-25-ty}{+0.017}
972
+ \mset{mjd-m5s-25-ty-k}{7/10}
973
+ \mset{mjd-m5s-25-ty-p}{0.032}
974
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975
+ \mset{mjd-m5s-25-yt}{$-$0.017}
976
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977
+ \mset{mjd-m5s-25-yt-p}{0.001}
978
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979
+ \mset{mj-m5s-100-tt}{0.688}
980
+ \mset{mj-m5s-100-ty}{0.745}
981
+ \mset{mj-m5s-100-yt}{0.642}
982
+ \mset{pd25-m5b-m5s-yy}{$-$0.020}
983
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984
+ \mset{pd25-m5b-m5s-yy-p}{0.010}
985
+ \mset{pd25-m5b-m5s-tt}{$-$0.019}
986
+ \mset{pd25-m5b-m5s-tt-k}{1/10}
987
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988
+ \mset{pd25-m5b-m5s-ty}{+0.012}
989
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990
+ \mset{pd25-m5b-m5s-ty-p}{0.065}
991
+ \mset{pd25-m5b-m5s-yt}{$-$0.001}
992
+ \mset{pd25-m5b-m5s-yt-k}{4/10}
993
+ \mset{pd25-m5b-m5s-yt-p}{0.312}
994
+ \mset{inv-done}{25}
995
+ \mset{inv-running}{4}
996
+ \mset{inv-queued}{0}
997
+ \mset{inv-planned}{0}
998
+ \mset{inv-stopped}{2}
999
+ \mset{inv-dropped}{4}
1000
+ \mset{inv-n}{35}
1001
+ \mset{inv-asof}{Mon 5 Oct, 15:00 AEDT}
1002
+ \mset{inv-eta-D1}{10:12}
1003
+ \mset{inv-eta-D2}{10:15}
1004
+ \mset{inv-eta-K2-Y}{11:49}
1005
+ \mset{inv-eta-K3-Y}{12:04}
1006
+ \mset{inv-eta-D18F}{09:14}
1007
+ \mset{inv-eta-SSLF}{10:38}
1008
+ \mset{inv-eta-K3-TB}{13:09}
1009
+ \mset{inv-eta-K3-TP}{14:03}
1010
+ \mset{inv-eta-J-B25}{14:45}
1011
+ \mset{inv-eta-J-S25}{15:06}
1012
+ \mset{inv-eta-K1}{16:17}
1013
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1014
+ \mset{inv-eta-K4-S}{17:42}
1015
+ \mset{inv-eta-K4-B}{19:46}
1016
+ \mset{inv-eta-J-B50}{18:51}
1017
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1018
+ \mset{inv-eta-K2-TP}{15:37}
1019
+ \mset{inv-eta-K2-TB}{18:05}
1020
+ \mset{inv-eta-M6B}{21:00}
1021
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1022
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1023
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1024
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1025
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1026
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1027
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1028
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1029
+ \mset{inv-eta-V5S}{18:45}
1030
+ \mset{inv-eta-V5B}{23:20}
1031
+ \mset{inv-lanes}{{extraction box},{GPU box 2, GPU 1},{GPU box 2, GPU 0},{GPU box 1, GPU 2},{GPU box 1, GPU 1},{GPU box 1, GPU 0}}
1032
+ \mset{m5b25-yy}{0.837}
1033
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1034
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1035
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1036
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1037
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1038
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1039
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1040
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1041
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1042
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1043
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1044
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1045
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1046
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1047
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1048
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1049
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1050
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1051
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1052
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1053
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1054
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1055
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1056
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1057
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1058
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1059
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1060
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1061
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1062
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1063
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1064
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1065
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1066
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1067
+ \mset{m5s25-n}{10}
1068
+ \mset{k1s-yy}{0.834}
1069
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1070
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1071
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1072
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1073
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1074
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1075
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1076
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1077
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1078
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1079
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1080
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1081
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1082
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1083
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1084
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1085
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1086
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1087
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1088
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1089
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1090
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1091
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1092
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1093
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1094
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1095
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1096
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1097
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1098
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1099
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1100
+ \mset{m5b75-ty-sd}{0.011}
1101
+ \mset{m5b75-yt}{0.640}
1102
+ \mset{m5b75-yt-sd}{0.004}
1103
+ \mset{m5b75-n}{10}
1104
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1105
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1106
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1107
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1108
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1109
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1110
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1111
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1112
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1113
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1114
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1115
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1116
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1117
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1118
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1119
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1120
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1121
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1122
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1123
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1124
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1125
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1126
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1127
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1128
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1129
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1130
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1131
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1132
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1133
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1134
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1135
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1136
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1137
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1138
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1139
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1140
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1141
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1142
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1143
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1144
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1145
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1146
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1147
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1148
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1149
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1150
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1151
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1152
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1153
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1154
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1155
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1156
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1157
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1158
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1159
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1160
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1161
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1162
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1163
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1164
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1165
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1166
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1167
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1168
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1169
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1170
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1171
+ \mset{m6ef-ty}{0.756}
1172
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1173
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1174
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1175
+ \mset{m6ef-n}{10}
1176
+ \mset{m6ec-yy}{0.819}
1177
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1178
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1179
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1180
+ \mset{m6ec-ty}{0.752}
1181
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1182
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1183
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1184
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1185
+ \mset{v4s-yy}{0.803}
1186
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1187
+ \mset{v4s-tt}{0.689}
1188
+ \mset{v4s-tt-sd}{0.018}
1189
+ \mset{v4s-ty}{0.777}
1190
+ \mset{v4s-ty-sd}{0.006}
1191
+ \mset{v4s-yt}{0.629}
1192
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1193
+ \mset{v4s-n}{10}
1194
+ \mset{v4b-yy}{0.846}
1195
+ \mset{v4b-yy-sd}{0.011}
1196
+ \mset{v4b-tt}{0.687}
1197
+ \mset{v4b-tt-sd}{0.013}
1198
+ \mset{v4b-ty}{0.758}
1199
+ \mset{v4b-ty-sd}{0.026}
1200
+ \mset{v4b-yt}{0.638}
1201
+ \mset{v4b-yt-sd}{0.007}
1202
+ \mset{v4b-n}{10}
1203
+ \mset{v4so1-yy}{0.815}
1204
+ \mset{v4so1-yy-sd}{0.014}
1205
+ \mset{v4so1-tt}{0.681}
1206
+ \mset{v4so1-tt-sd}{0.012}
1207
+ \mset{v4so1-ty}{0.738}
1208
+ \mset{v4so1-ty-sd}{0.017}
1209
+ \mset{v4so1-yt}{0.629}
1210
+ \mset{v4so1-yt-sd}{0.007}
1211
+ \mset{v4so1-n}{10}
1212
+ \mset{m6gc0-yy}{0.816}
1213
+ \mset{m6gc0-yy-sd}{0.016}
1214
+ \mset{m6gc0-tt}{0.663}
1215
+ \mset{m6gc0-tt-sd}{0.015}
1216
+ \mset{m6gc0-ty}{0.760}
1217
+ \mset{m6gc0-ty-sd}{0.023}
1218
+ \mset{m6gc0-yt}{0.616}
1219
+ \mset{m6gc0-yt-sd}{0.007}
1220
+ \mset{m6gc0-n}{10}
1221
+ \mset{m6gc1-yy}{0.819}
1222
+ \mset{m6gc1-yy-sd}{0.010}
1223
+ \mset{m6gc1-tt}{0.659}
1224
+ \mset{m6gc1-tt-sd}{0.016}
1225
+ \mset{m6gc1-ty}{0.773}
1226
+ \mset{m6gc1-ty-sd}{0.022}
1227
+ \mset{m6gc1-yt}{0.614}
1228
+ \mset{m6gc1-yt-sd}{0.008}
1229
+ \mset{m6gc1-n}{10}
1230
+ \mset{m6gc2-yy}{0.826}
1231
+ \mset{m6gc2-yy-sd}{0.012}
1232
+ \mset{m6gc2-tt}{0.652}
1233
+ \mset{m6gc2-tt-sd}{0.017}
1234
+ \mset{m6gc2-ty}{0.766}
1235
+ \mset{m6gc2-ty-sd}{0.023}
1236
+ \mset{m6gc2-yt}{0.615}
1237
+ \mset{m6gc2-yt-sd}{0.007}
1238
+ \mset{m6gc2-n}{10}
1239
+ \mset{m6gz0-yy}{0.795}
1240
+ \mset{m6gz0-yy-sd}{0.015}
1241
+ \mset{m6gz0-tt}{0.664}
1242
+ \mset{m6gz0-tt-sd}{0.010}
1243
+ \mset{m6gz0-ty}{0.766}
1244
+ \mset{m6gz0-ty-sd}{0.018}
1245
+ \mset{m6gz0-yt}{0.610}
1246
+ \mset{m6gz0-yt-sd}{0.012}
1247
+ \mset{m6gz0-n}{10}
1248
+ \mset{m6gz1-yy}{0.814}
1249
+ \mset{m6gz1-yy-sd}{0.013}
1250
+ \mset{m6gz1-tt}{0.660}
1251
+ \mset{m6gz1-tt-sd}{0.016}
1252
+ \mset{m6gz1-ty}{0.775}
1253
+ \mset{m6gz1-ty-sd}{0.017}
1254
+ \mset{m6gz1-yt}{0.612}
1255
+ \mset{m6gz1-yt-sd}{0.011}
1256
+ \mset{m6gz1-n}{10}
1257
+ \mset{m6gz2-yy}{0.810}
1258
+ \mset{m6gz2-yy-sd}{0.025}
1259
+ \mset{m6gz2-tt}{0.663}
1260
+ \mset{m6gz2-tt-sd}{0.018}
1261
+ \mset{m6gz2-ty}{0.773}
1262
+ \mset{m6gz2-ty-sd}{0.011}
1263
+ \mset{m6gz2-yt}{0.603}
1264
+ \mset{m6gz2-yt-sd}{0.010}
1265
+ \mset{m6gz2-n}{10}
1266
+ \mset{v5s-yy}{0.807}
1267
+ \mset{v5s-yy-sd}{0.020}
1268
+ \mset{v5s-tt}{0.690}
1269
+ \mset{v5s-tt-sd}{0.014}
1270
+ \mset{v5s-ty}{0.753}
1271
+ \mset{v5s-ty-sd}{0.008}
1272
+ \mset{v5s-yt}{0.620}
1273
+ \mset{v5s-yt-sd}{0.009}
1274
+ \mset{v5s-n}{10}
1275
+ \mset{v5b-yy}{0.832}
1276
+ \mset{v5b-yy-sd}{0.017}
1277
+ \mset{v5b-tt}{0.701}
1278
+ \mset{v5b-tt-sd}{0.014}
1279
+ \mset{v5b-ty}{0.755}
1280
+ \mset{v5b-ty-sd}{0.023}
1281
+ \mset{v5b-yt}{0.638}
1282
+ \mset{v5b-yt-sd}{0.003}
1283
+ \mset{v5b-n}{10}
1284
+ \mset{v5so1-yy}{0.811}
1285
+ \mset{v5so1-yy-sd}{0.014}
1286
+ \mset{v5so1-tt}{0.699}
1287
+ \mset{v5so1-tt-sd}{0.016}
1288
+ \mset{v5so1-ty}{0.751}
1289
+ \mset{v5so1-ty-sd}{0.013}
1290
+ \mset{v5so1-yt}{0.626}
1291
+ \mset{v5so1-yt-sd}{0.006}
1292
+ \mset{v5so1-n}{10}
1293
+ \mset{v5so2-yy}{0.805}
1294
+ \mset{v5so2-yy-sd}{0.019}
1295
+ \mset{v5so2-tt}{0.682}
1296
+ \mset{v5so2-tt-sd}{0.017}
1297
+ \mset{v5so2-ty}{0.747}
1298
+ \mset{v5so2-ty-sd}{0.010}
1299
+ \mset{v5so2-yt}{0.628}
1300
+ \mset{v5so2-yt-sd}{0.009}
1301
+ \mset{v5so2-n}{10}
1302
+ \mset{v5bo1-yy}{0.840}
1303
+ \mset{v5bo1-yy-sd}{0.016}
1304
+ \mset{v5bo1-tt}{0.696}
1305
+ \mset{v5bo1-tt-sd}{0.015}
1306
+ \mset{v5bo1-ty}{0.773}
1307
+ \mset{v5bo1-ty-sd}{0.011}
1308
+ \mset{v5bo1-yt}{0.633}
1309
+ \mset{v5bo1-yt-sd}{0.007}
1310
+ \mset{v5bo1-n}{10}
1311
+ \mset{soupv4s-yy}{0.808}
1312
+ \mset{soupv4s-yy-sd}{0.012}
1313
+ \mset{soupv4s-tt}{0.695}
1314
+ \mset{soupv4s-tt-sd}{0.019}
1315
+ \mset{soupv4s-ty}{0.746}
1316
+ \mset{soupv4s-ty-sd}{0.019}
1317
+ \mset{soupv4s-yt}{0.623}
1318
+ \mset{soupv4s-yt-sd}{0.008}
1319
+ \mset{soupv4s-n}{10}
1320
+ \mset{soupb-yy}{0.824}
1321
+ \mset{soupb-yy-sd}{0.015}
1322
+ \mset{soupb-tt}{0.701}
1323
+ \mset{soupb-tt-sd}{0.011}
1324
+ \mset{soupb-ty}{0.778}
1325
+ \mset{soupb-ty-sd}{0.014}
1326
+ \mset{soupb-yt}{0.643}
1327
+ \mset{soupb-yt-sd}{0.006}
1328
+ \mset{soupb-n}{10}
1329
+ \mset{soupg-yy}{0.816}
1330
+ \mset{soupg-yy-sd}{0.012}
1331
+ \mset{soupg-tt}{0.666}
1332
+ \mset{soupg-tt-sd}{0.015}
1333
+ \mset{soupg-ty}{0.769}
1334
+ \mset{soupg-ty-sd}{0.017}
1335
+ \mset{soupg-yt}{0.615}
1336
+ \mset{soupg-yt-sd}{0.007}
1337
+ \mset{soupg-n}{10}
1338
+ \mset{m6kc0-yy}{0.808}
1339
+ \mset{m6kc0-yy-sd}{0.011}
1340
+ \mset{m6kc0-tt}{0.672}
1341
+ \mset{m6kc0-tt-sd}{0.017}
1342
+ \mset{m6kc0-ty}{0.722}
1343
+ \mset{m6kc0-ty-sd}{0.021}
1344
+ \mset{m6kc0-yt}{0.608}
1345
+ \mset{m6kc0-yt-sd}{0.007}
1346
+ \mset{m6kc0-n}{10}
1347
+ \mset{m6kc1-n}{0}
1348
+ \mset{m6kz0-n}{0}
1349
+ \mset{m6kz1-n}{0}
1350
+ \mset{jms3-yy}{0.832}
1351
+ \mset{jms3-yy-sd}{0.015}
1352
+ \mset{jms3-tt}{0.679}
1353
+ \mset{jms3-tt-sd}{0.013}
1354
+ \mset{jms3-ty}{0.798}
1355
+ \mset{jms3-ty-sd}{0.019}
1356
+ \mset{jms3-yt}{0.646}
1357
+ \mset{jms3-yt-sd}{0.005}
1358
+ \mset{jms3-n}{10}
1359
+ \mset{jms4-yy}{0.826}
1360
+ \mset{jms4-yy-sd}{0.014}
1361
+ \mset{jms4-tt}{0.678}
1362
+ \mset{jms4-tt-sd}{0.018}
1363
+ \mset{jms4-ty}{0.797}
1364
+ \mset{jms4-ty-sd}{0.013}
1365
+ \mset{jms4-yt}{0.644}
1366
+ \mset{jms4-yt-sd}{0.006}
1367
+ \mset{jms4-n}{10}
1368
+ \mset{jms3k2-yy}{0.840}
1369
+ \mset{jms3k2-yy-sd}{0.008}
1370
+ \mset{jms3k2-tt}{0.680}
1371
+ \mset{jms3k2-tt-sd}{0.013}
1372
+ \mset{jms3k2-ty}{0.795}
1373
+ \mset{jms3k2-ty-sd}{0.014}
1374
+ \mset{jms3k2-yt}{0.652}
1375
+ \mset{jms3k2-yt-sd}{0.009}
1376
+ \mset{jms3k2-n}{10}
1377
+ \mset{jms4k2-yy}{0.835}
1378
+ \mset{jms4k2-yy-sd}{0.013}
1379
+ \mset{jms4k2-tt}{0.679}
1380
+ \mset{jms4k2-tt-sd}{0.015}
1381
+ \mset{jms4k2-ty}{0.790}
1382
+ \mset{jms4k2-ty-sd}{0.016}
1383
+ \mset{jms4k2-yt}{0.656}
1384
+ \mset{jms4k2-yt-sd}{0.006}
1385
+ \mset{jms4k2-n}{10}
1386
+ \mset{jmb3-yy}{0.834}
1387
+ \mset{jmb3-yy-sd}{0.013}
1388
+ \mset{jmb3-tt}{0.682}
1389
+ \mset{jmb3-tt-sd}{0.017}
1390
+ \mset{jmb3-ty}{0.789}
1391
+ \mset{jmb3-ty-sd}{0.019}
1392
+ \mset{jmb3-yt}{0.642}
1393
+ \mset{jmb3-yt-sd}{0.006}
1394
+ \mset{jmb3-n}{10}
1395
+ \mset{jmb4-yy}{0.827}
1396
+ \mset{jmb4-yy-sd}{0.009}
1397
+ \mset{jmb4-tt}{0.680}
1398
+ \mset{jmb4-tt-sd}{0.019}
1399
+ \mset{jmb4-ty}{0.785}
1400
+ \mset{jmb4-ty-sd}{0.016}
1401
+ \mset{jmb4-yt}{0.643}
1402
+ \mset{jmb4-yt-sd}{0.006}
1403
+ \mset{jmb4-n}{10}
1404
+ \mset{jmb3k2-yy}{0.795}
1405
+ \mset{jmb3k2-yy-sd}{0.016}
1406
+ \mset{jmb3k2-tt}{0.662}
1407
+ \mset{jmb3k2-tt-sd}{0.026}
1408
+ \mset{jmb3k2-ty}{0.745}
1409
+ \mset{jmb3k2-ty-sd}{0.027}
1410
+ \mset{jmb3k2-yt}{0.623}
1411
+ \mset{jmb3k2-yt-sd}{0.008}
1412
+ \mset{jmb3k2-n}{10}
1413
+ \mset{jlr3-yy}{0.831}
1414
+ \mset{jlr3-yy-sd}{0.022}
1415
+ \mset{jlr3-tt}{0.685}
1416
+ \mset{jlr3-tt-sd}{0.020}
1417
+ \mset{jlr3-ty}{0.784}
1418
+ \mset{jlr3-ty-sd}{0.009}
1419
+ \mset{jlr3-yt}{0.651}
1420
+ \mset{jlr3-yt-sd}{0.007}
1421
+ \mset{jlr3-n}{10}
1422
+ \mset{jv5-yy}{0.821}
1423
+ \mset{jv5-yy-sd}{0.019}
1424
+ \mset{jv5-tt}{0.685}
1425
+ \mset{jv5-tt-sd}{0.009}
1426
+ \mset{jv5-ty}{0.772}
1427
+ \mset{jv5-ty-sd}{0.014}
1428
+ \mset{jv5-yt}{0.626}
1429
+ \mset{jv5-yt-sd}{0.009}
1430
+ \mset{jv5-n}{10}
1431
+ \mset{jsh3-yy}{0.809}
1432
+ \mset{jsh3-yy-sd}{0.018}
1433
+ \mset{jsh3-tt}{0.687}
1434
+ \mset{jsh3-tt-sd}{0.014}
1435
+ \mset{jsh3-ty}{0.791}
1436
+ \mset{jsh3-ty-sd}{0.010}
1437
+ \mset{jsh3-yt}{0.653}
1438
+ \mset{jsh3-yt-sd}{0.009}
1439
+ \mset{jsh3-n}{10}
1440
+ \mset{jsh4-yy}{0.808}
1441
+ \mset{jsh4-yy-sd}{0.019}
1442
+ \mset{jsh4-tt}{0.684}
1443
+ \mset{jsh4-tt-sd}{0.017}
1444
+ \mset{jsh4-ty}{0.790}
1445
+ \mset{jsh4-ty-sd}{0.011}
1446
+ \mset{jsh4-yt}{0.654}
1447
+ \mset{jsh4-yt-sd}{0.007}
1448
+ \mset{jsh4-n}{10}
1449
+ \mset{jbsh3-yy}{0.775}
1450
+ \mset{jbsh3-yy-sd}{0.036}
1451
+ \mset{jbsh3-tt}{0.655}
1452
+ \mset{jbsh3-tt-sd}{0.027}
1453
+ \mset{jbsh3-ty}{0.762}
1454
+ \mset{jbsh3-ty-sd}{0.010}
1455
+ \mset{jbsh3-yt}{0.628}
1456
+ \mset{jbsh3-yt-sd}{0.013}
1457
+ \mset{jbsh3-n}{10}
1458
+ \mset{jbsh4-yy}{0.789}
1459
+ \mset{jbsh4-yy-sd}{0.029}
1460
+ \mset{jbsh4-tt}{0.662}
1461
+ \mset{jbsh4-tt-sd}{0.017}
1462
+ \mset{jbsh4-ty}{0.761}
1463
+ \mset{jbsh4-ty-sd}{0.013}
1464
+ \mset{jbsh4-yt}{0.629}
1465
+ \mset{jbsh4-yt-sd}{0.016}
1466
+ \mset{jbsh4-n}{10}
1467
+ \mset{j25s3-yy}{0.848}
1468
+ \mset{j25s3-yy-sd}{0.015}
1469
+ \mset{j25s3-tt}{0.689}
1470
+ \mset{j25s3-tt-sd}{0.014}
1471
+ \mset{j25s3-ty}{0.798}
1472
+ \mset{j25s3-ty-sd}{0.011}
1473
+ \mset{j25s3-yt}{0.642}
1474
+ \mset{j25s3-yt-sd}{0.009}
1475
+ \mset{j25s3-n}{10}
1476
+ \mset{j25s4-yy}{0.851}
1477
+ \mset{j25s4-yy-sd}{0.014}
1478
+ \mset{j25s4-tt}{0.687}
1479
+ \mset{j25s4-tt-sd}{0.019}
1480
+ \mset{j25s4-ty}{0.792}
1481
+ \mset{j25s4-ty-sd}{0.016}
1482
+ \mset{j25s4-yt}{0.642}
1483
+ \mset{j25s4-yt-sd}{0.008}
1484
+ \mset{j25s4-n}{10}
1485
+ \mset{j25s5-yy}{0.850}
1486
+ \mset{j25s5-yy-sd}{0.012}
1487
+ \mset{j25s5-tt}{0.687}
1488
+ \mset{j25s5-tt-sd}{0.018}
1489
+ \mset{j25s5-ty}{0.795}
1490
+ \mset{j25s5-ty-sd}{0.014}
1491
+ \mset{j25s5-yt}{0.643}
1492
+ \mset{j25s5-yt-sd}{0.008}
1493
+ \mset{j25s5-n}{10}
1494
+ \mset{jj25s3-yy}{0.844}
1495
+ \mset{jj25s3-yy-sd}{0.022}
1496
+ \mset{jj25s3-tt}{0.690}
1497
+ \mset{jj25s3-tt-sd}{0.012}
1498
+ \mset{jj25s3-ty}{0.812}
1499
+ \mset{jj25s3-ty-sd}{0.015}
1500
+ \mset{jj25s3-yt}{0.650}
1501
+ \mset{jj25s3-yt-sd}{0.008}
1502
+ \mset{jj25s3-n}{10}
1503
+ \mset{jj25s4-yy}{0.847}
1504
+ \mset{jj25s4-yy-sd}{0.018}
1505
+ \mset{jj25s4-tt}{0.681}
1506
+ \mset{jj25s4-tt-sd}{0.016}
1507
+ \mset{jj25s4-ty}{0.812}
1508
+ \mset{jj25s4-ty-sd}{0.010}
1509
+ \mset{jj25s4-yt}{0.651}
1510
+ \mset{jj25s4-yt-sd}{0.006}
1511
+ \mset{jj25s4-n}{10}
1512
+ \mset{jj25s5-yy}{0.853}
1513
+ \mset{jj25s5-yy-sd}{0.019}
1514
+ \mset{jj25s5-tt}{0.685}
1515
+ \mset{jj25s5-tt-sd}{0.013}
1516
+ \mset{jj25s5-ty}{0.810}
1517
+ \mset{jj25s5-ty-sd}{0.015}
1518
+ \mset{jj25s5-yt}{0.652}
1519
+ \mset{jj25s5-yt-sd}{0.007}
1520
+ \mset{jj25s5-n}{10}
1521
+ \mset{jj25s3b-yy}{0.846}
1522
+ \mset{jj25s3b-yy-sd}{0.016}
1523
+ \mset{jj25s3b-tt}{0.682}
1524
+ \mset{jj25s3b-tt-sd}{0.018}
1525
+ \mset{jj25s3b-ty}{0.807}
1526
+ \mset{jj25s3b-ty-sd}{0.016}
1527
+ \mset{jj25s3b-yt}{0.650}
1528
+ \mset{jj25s3b-yt-sd}{0.006}
1529
+ \mset{jj25s3b-n}{10}
1530
+ \mset{j100s4-yy}{0.863}
1531
+ \mset{j100s4-yy-sd}{0.018}
1532
+ \mset{j100s4-tt}{0.669}
1533
+ \mset{j100s4-tt-sd}{0.021}
1534
+ \mset{j100s4-ty}{0.772}
1535
+ \mset{j100s4-ty-sd}{0.019}
1536
+ \mset{j100s4-yt}{0.637}
1537
+ \mset{j100s4-yt-sd}{0.005}
1538
+ \mset{j100s4-n}{10}
1539
+ \mset{jj100s3-yy}{0.843}
1540
+ \mset{jj100s3-yy-sd}{0.020}
1541
+ \mset{jj100s3-tt}{0.667}
1542
+ \mset{jj100s3-tt-sd}{0.020}
1543
+ \mset{jj100s3-ty}{0.775}
1544
+ \mset{jj100s3-ty-sd}{0.017}
1545
+ \mset{jj100s3-yt}{0.642}
1546
+ \mset{jj100s3-yt-sd}{0.004}
1547
+ \mset{jj100s3-n}{10}
1548
+ \mset{jj100s4-yy}{0.838}
1549
+ \mset{jj100s4-yy-sd}{0.013}
1550
+ \mset{jj100s4-tt}{0.668}
1551
+ \mset{jj100s4-tt-sd}{0.011}
1552
+ \mset{jj100s4-ty}{0.768}
1553
+ \mset{jj100s4-ty-sd}{0.017}
1554
+ \mset{jj100s4-yt}{0.639}
1555
+ \mset{jj100s4-yt-sd}{0.006}
1556
+ \mset{jj100s4-n}{10}
1557
+ \mset{jj100s3b-yy}{0.840}
1558
+ \mset{jj100s3b-yy-sd}{0.009}
1559
+ \mset{jj100s3b-tt}{0.663}
1560
+ \mset{jj100s3b-tt-sd}{0.014}
1561
+ \mset{jj100s3b-ty}{0.776}
1562
+ \mset{jj100s3b-ty-sd}{0.027}
1563
+ \mset{jj100s3b-yt}{0.641}
1564
+ \mset{jj100s3b-yt-sd}{0.006}
1565
+ \mset{jj100s3b-n}{10}
1566
+ \mset{jj50s-yy}{0.871}
1567
+ \mset{jj50s-yy-sd}{0.013}
1568
+ \mset{jj50s-tt}{0.661}
1569
+ \mset{jj50s-tt-sd}{0.021}
1570
+ \mset{jj50s-ty}{0.775}
1571
+ \mset{jj50s-ty-sd}{0.023}
1572
+ \mset{jj50s-yt}{0.649}
1573
+ \mset{jj50s-yt-sd}{0.003}
1574
+ \mset{jj50s-n}{10}
1575
+ \mset{jjm6d-yy}{0.827}
1576
+ \mset{jjm6d-yy-sd}{0.008}
1577
+ \mset{jjm6d-tt}{0.673}
1578
+ \mset{jjm6d-tt-sd}{0.017}
1579
+ \mset{jjm6d-ty}{0.806}
1580
+ \mset{jjm6d-ty-sd}{0.017}
1581
+ \mset{jjm6d-yt}{0.649}
1582
+ \mset{jjm6d-yt-sd}{0.006}
1583
+ \mset{jjm6d-n}{10}
1584
+ \mset{jjb-yy}{0.832}
1585
+ \mset{jjb-yy-sd}{0.013}
1586
+ \mset{jjb-tt}{0.673}
1587
+ \mset{jjb-tt-sd}{0.019}
1588
+ \mset{jjb-ty}{0.786}
1589
+ \mset{jjb-ty-sd}{0.010}
1590
+ \mset{jjb-yt}{0.639}
1591
+ \mset{jjb-yt-sd}{0.007}
1592
+ \mset{jjb-n}{10}
1593
+ \mset{j100b-n}{0}
1594
+ \mset{e999-yy}{0.854}
1595
+ \mset{e999-yy-sd}{0.017}
1596
+ \mset{e999-tt}{0.665}
1597
+ \mset{e999-tt-sd}{0.015}
1598
+ \mset{e999-ty}{0.801}
1599
+ \mset{e999-ty-sd}{0.029}
1600
+ \mset{e999-yt}{0.644}
1601
+ \mset{e999-yt-sd}{0.005}
1602
+ \mset{e999-n}{10}
1603
+ \mset{e999s4-yy}{0.865}
1604
+ \mset{e999s4-yy-sd}{0.018}
1605
+ \mset{e999s4-tt}{0.671}
1606
+ \mset{e999s4-tt-sd}{0.013}
1607
+ \mset{e999s4-ty}{0.811}
1608
+ \mset{e999s4-ty-sd}{0.015}
1609
+ \mset{e999s4-yt}{0.643}
1610
+ \mset{e999s4-yt-sd}{0.005}
1611
+ \mset{e999s4-n}{10}
1612
+ \mset{e9995-yy}{0.855}
1613
+ \mset{e9995-yy-sd}{0.014}
1614
+ \mset{e9995-tt}{0.669}
1615
+ \mset{e9995-tt-sd}{0.023}
1616
+ \mset{e9995-ty}{0.803}
1617
+ \mset{e9995-ty-sd}{0.011}
1618
+ \mset{e9995-yt}{0.648}
1619
+ \mset{e9995-yt-sd}{0.007}
1620
+ \mset{e9995-n}{10}
1621
+ \mset{e9995l-yy}{0.850}
1622
+ \mset{e9995l-yy-sd}{0.018}
1623
+ \mset{e9995l-tt}{0.657}
1624
+ \mset{e9995l-tt-sd}{0.019}
1625
+ \mset{e9995l-ty}{0.807}
1626
+ \mset{e9995l-ty-sd}{0.021}
1627
+ \mset{e9995l-yt}{0.646}
1628
+ \mset{e9995l-yt-sd}{0.004}
1629
+ \mset{e9995l-n}{10}
1630
+ \mset{e9995h-yy}{0.842}
1631
+ \mset{e9995h-yy-sd}{0.014}
1632
+ \mset{e9995h-tt}{0.667}
1633
+ \mset{e9995h-tt-sd}{0.016}
1634
+ \mset{e9995h-ty}{0.788}
1635
+ \mset{e9995h-ty-sd}{0.010}
1636
+ \mset{e9995h-yt}{0.630}
1637
+ \mset{e9995h-yt-sd}{0.006}
1638
+ \mset{e9995h-n}{10}
1639
+ \mset{e9995s4-yy}{0.862}
1640
+ \mset{e9995s4-yy-sd}{0.015}
1641
+ \mset{e9995s4-tt}{0.669}
1642
+ \mset{e9995s4-tt-sd}{0.018}
1643
+ \mset{e9995s4-ty}{0.801}
1644
+ \mset{e9995s4-ty-sd}{0.012}
1645
+ \mset{e9995s4-yt}{0.648}
1646
+ \mset{e9995s4-yt-sd}{0.006}
1647
+ \mset{e9995s4-n}{10}
1648
+ \mset{e999l-yy}{0.853}
1649
+ \mset{e999l-yy-sd}{0.018}
1650
+ \mset{e999l-tt}{0.660}
1651
+ \mset{e999l-tt-sd}{0.020}
1652
+ \mset{e999l-ty}{0.811}
1653
+ \mset{e999l-ty-sd}{0.015}
1654
+ \mset{e999l-yt}{0.635}
1655
+ \mset{e999l-yt-sd}{0.005}
1656
+ \mset{e999l-n}{10}
1657
+ \mset{e999s5-yy}{0.859}
1658
+ \mset{e999s5-yy-sd}{0.011}
1659
+ \mset{e999s5-tt}{0.662}
1660
+ \mset{e999s5-tt-sd}{0.017}
1661
+ \mset{e999s5-ty}{0.799}
1662
+ \mset{e999s5-ty-sd}{0.013}
1663
+ \mset{e999s5-yt}{0.642}
1664
+ \mset{e999s5-yt-sd}{0.004}
1665
+ \mset{e999s5-n}{10}
1666
+ \mset{e999s6-yy}{0.856}
1667
+ \mset{e999s6-yy-sd}{0.011}
1668
+ \mset{e999s6-tt}{0.659}
1669
+ \mset{e999s6-tt-sd}{0.017}
1670
+ \mset{e999s6-ty}{0.810}
1671
+ \mset{e999s6-ty-sd}{0.014}
1672
+ \mset{e999s6-yt}{0.640}
1673
+ \mset{e999s6-yt-sd}{0.006}
1674
+ \mset{e999s6-n}{10}
1675
+ \mset{mixa75-yy}{0.847}
1676
+ \mset{mixa75-yy-sd}{0.022}
1677
+ \mset{mixa75-tt}{0.677}
1678
+ \mset{mixa75-tt-sd}{0.024}
1679
+ \mset{mixa75-ty}{0.794}
1680
+ \mset{mixa75-ty-sd}{0.018}
1681
+ \mset{mixa75-yt}{0.651}
1682
+ \mset{mixa75-yt-sd}{0.004}
1683
+ \mset{mixa75-n}{10}
1684
+ \mset{mixa50-yy}{0.846}
1685
+ \mset{mixa50-yy-sd}{0.014}
1686
+ \mset{mixa50-tt}{0.669}
1687
+ \mset{mixa50-tt-sd}{0.020}
1688
+ \mset{mixa50-ty}{0.794}
1689
+ \mset{mixa50-ty-sd}{0.013}
1690
+ \mset{mixa50-yt}{0.647}
1691
+ \mset{mixa50-yt-sd}{0.003}
1692
+ \mset{mixa50-n}{10}
1693
+ \mset{xtf-yy}{0.842}
1694
+ \mset{xtf-yy-sd}{0.020}
1695
+ \mset{xtf-tt}{0.664}
1696
+ \mset{xtf-tt-sd}{0.024}
1697
+ \mset{xtf-ty}{0.802}
1698
+ \mset{xtf-ty-sd}{0.010}
1699
+ \mset{xtf-yt}{0.641}
1700
+ \mset{xtf-yt-sd}{0.004}
1701
+ \mset{xtf-n}{10}
1702
+ \mset{xth-yy}{0.844}
1703
+ \mset{xth-yy-sd}{0.012}
1704
+ \mset{xth-tt}{0.653}
1705
+ \mset{xth-tt-sd}{0.012}
1706
+ \mset{xth-ty}{0.793}
1707
+ \mset{xth-ty-sd}{0.023}
1708
+ \mset{xth-yt}{0.638}
1709
+ \mset{xth-yt-sd}{0.004}
1710
+ \mset{xth-n}{10}
1711
+ \mset{wisea75-yy}{0.855}
1712
+ \mset{wisea75-yy-sd}{0.011}
1713
+ \mset{wisea75-tt}{0.687}
1714
+ \mset{wisea75-tt-sd}{0.010}
1715
+ \mset{wisea75-ty}{0.800}
1716
+ \mset{wisea75-ty-sd}{0.012}
1717
+ \mset{wisea75-yt}{0.647}
1718
+ \mset{wisea75-yt-sd}{0.007}
1719
+ \mset{wisea75-n}{10}
1720
+ \mset{wisea50-yy}{0.859}
1721
+ \mset{wisea50-yy-sd}{0.017}
1722
+ \mset{wisea50-tt}{0.693}
1723
+ \mset{wisea50-tt-sd}{0.013}
1724
+ \mset{wisea50-ty}{0.797}
1725
+ \mset{wisea50-ty-sd}{0.008}
1726
+ \mset{wisea50-yt}{0.645}
1727
+ \mset{wisea50-yt-sd}{0.006}
1728
+ \mset{wisea50-n}{10}
1729
+ \mset{jjj25s3-yy}{0.834}
1730
+ \mset{jjj25s3-yy-sd}{0.019}
1731
+ \mset{jjj25s3-tt}{0.674}
1732
+ \mset{jjj25s3-tt-sd}{0.015}
1733
+ \mset{jjj25s3-ty}{0.806}
1734
+ \mset{jjj25s3-ty-sd}{0.019}
1735
+ \mset{jjj25s3-yt}{0.654}
1736
+ \mset{jjj25s3-yt-sd}{0.004}
1737
+ \mset{jjj25s3-n}{10}
1738
+ \mset{jaug25-yy}{0.842}
1739
+ \mset{jaug25-yy-sd}{0.015}
1740
+ \mset{jaug25-tt}{0.670}
1741
+ \mset{jaug25-tt-sd}{0.020}
1742
+ \mset{jaug25-ty}{0.751}
1743
+ \mset{jaug25-ty-sd}{0.018}
1744
+ \mset{jaug25-yt}{0.600}
1745
+ \mset{jaug25-yt-sd}{0.008}
1746
+ \mset{jaug25-n}{10}
1747
+ \mset{j25aug-yy}{0.847}
1748
+ \mset{j25aug-yy-sd}{0.016}
1749
+ \mset{j25aug-tt}{0.685}
1750
+ \mset{j25aug-tt-sd}{0.015}
1751
+ \mset{j25aug-ty}{0.796}
1752
+ \mset{j25aug-ty-sd}{0.014}
1753
+ \mset{j25aug-yt}{0.646}
1754
+ \mset{j25aug-yt-sd}{0.009}
1755
+ \mset{j25aug-n}{10}
1756
+ \mset{j25blk-yy}{0.851}
1757
+ \mset{j25blk-yy-sd}{0.017}
1758
+ \mset{j25blk-tt}{0.682}
1759
+ \mset{j25blk-tt-sd}{0.023}
1760
+ \mset{j25blk-ty}{0.790}
1761
+ \mset{j25blk-ty-sd}{0.017}
1762
+ \mset{j25blk-yt}{0.643}
1763
+ \mset{j25blk-yt-sd}{0.008}
1764
+ \mset{j25blk-n}{10}
1765
+ \mset{j25lr2-yy}{0.849}
1766
+ \mset{j25lr2-yy-sd}{0.022}
1767
+ \mset{j25lr2-tt}{0.691}
1768
+ \mset{j25lr2-tt-sd}{0.016}
1769
+ \mset{j25lr2-ty}{0.781}
1770
+ \mset{j25lr2-ty-sd}{0.019}
1771
+ \mset{j25lr2-yt}{0.639}
1772
+ \mset{j25lr2-yt-sd}{0.007}
1773
+ \mset{j25lr2-n}{10}
1774
+ \mset{j2512k-yy}{0.854}
1775
+ \mset{j2512k-yy-sd}{0.024}
1776
+ \mset{j2512k-tt}{0.690}
1777
+ \mset{j2512k-tt-sd}{0.021}
1778
+ \mset{j2512k-ty}{0.787}
1779
+ \mset{j2512k-ty-sd}{0.015}
1780
+ \mset{j2512k-yt}{0.644}
1781
+ \mset{j2512k-yt-sd}{0.009}
1782
+ \mset{j2512k-n}{10}
1783
+ \mset{j100s-yy}{0.870}
1784
+ \mset{j100s-yy-sd}{0.014}
1785
+ \mset{j100s-tt}{0.673}
1786
+ \mset{j100s-tt-sd}{0.013}
1787
+ \mset{j100s-ty}{0.776}
1788
+ \mset{j100s-ty-sd}{0.015}
1789
+ \mset{j100s-yt}{0.638}
1790
+ \mset{j100s-yt-sd}{0.005}
1791
+ \mset{j100s-n}{10}
1792
+ \mset{j50s-yy}{0.858}
1793
+ \mset{j50s-yy-sd}{0.020}
1794
+ \mset{j50s-tt}{0.672}
1795
+ \mset{j50s-tt-sd}{0.021}
1796
+ \mset{j50s-ty}{0.778}
1797
+ \mset{j50s-ty-sd}{0.022}
1798
+ \mset{j50s-yt}{0.653}
1799
+ \mset{j50s-yt-sd}{0.005}
1800
+ \mset{j50s-n}{10}
1801
+ \mset{j75s-n}{0}
1802
+ \mset{j18k-n}{0}
1803
+ \mset{j25b-yy}{0.830}
1804
+ \mset{j25b-yy-sd}{0.022}
1805
+ \mset{j25b-tt}{0.673}
1806
+ \mset{j25b-tt-sd}{0.011}
1807
+ \mset{j25b-ty}{0.784}
1808
+ \mset{j25b-ty-sd}{0.012}
1809
+ \mset{j25b-yt}{0.630}
1810
+ \mset{j25b-yt-sd}{0.008}
1811
+ \mset{j25b-n}{10}
1812
+ \mset{j50b-n}{0}
1813
+ \mset{j75b-n}{0}
1814
+ \mset{jm6db-n}{0}
1815
+ \mset{m5s50-n}{0}
1816
+ \mset{m5s75-n}{0}
1817
+ \mset{rda-yy}{0.823}
1818
+ \mset{rda-yy-sd}{0.018}
1819
+ \mset{rda-tt}{0.686}
1820
+ \mset{rda-tt-sd}{0.013}
1821
+ \mset{rda-ty}{0.749}
1822
+ \mset{rda-ty-sd}{0.013}
1823
+ \mset{rda-yt}{0.625}
1824
+ \mset{rda-yt-sd}{0.008}
1825
+ \mset{rda-n}{10}
1826
+ \mset{rdb-yy}{0.816}
1827
+ \mset{rdb-yy-sd}{0.022}
1828
+ \mset{rdb-tt}{0.672}
1829
+ \mset{rdb-tt-sd}{0.022}
1830
+ \mset{rdb-ty}{0.750}
1831
+ \mset{rdb-ty-sd}{0.024}
1832
+ \mset{rdb-yt}{0.630}
1833
+ \mset{rdb-yt-sd}{0.014}
1834
+ \mset{rdb-n}{10}
1835
+ \mset{rdc-yy}{0.799}
1836
+ \mset{rdc-yy-sd}{0.009}
1837
+ \mset{rdc-tt}{0.690}
1838
+ \mset{rdc-tt-sd}{0.011}
1839
+ \mset{rdc-ty}{0.776}
1840
+ \mset{rdc-ty-sd}{0.016}
1841
+ \mset{rdc-yt}{0.626}
1842
+ \mset{rdc-yt-sd}{0.005}
1843
+ \mset{rdc-n}{10}
1844
+ \mset{rdctl-yy}{0.824}
1845
+ \mset{rdctl-yy-sd}{0.020}
1846
+ \mset{rdctl-tt}{0.681}
1847
+ \mset{rdctl-tt-sd}{0.022}
1848
+ \mset{rdctl-ty}{0.749}
1849
+ \mset{rdctl-ty-sd}{0.020}
1850
+ \mset{rdctl-yt}{0.623}
1851
+ \mset{rdctl-yt-sd}{0.007}
1852
+ \mset{rdctl-n}{10}
1853
+ \mset{pd-k1b-m5b25-yy}{$-$0.005}
1854
+ \mset{pd-k1b-m5b25-yy-k}{4/10}
1855
+ \mset{pd-k1b-m5b25-yy-p}{0.312}
1856
+ \mset{pd-k1b-m5b25-tt}{$-$0.010}
1857
+ \mset{pd-k1b-m5b25-tt-k}{3/10}
1858
+ \mset{pd-k1b-m5b25-tt-p}{0.116}
1859
+ \mset{pd-k1b-m5b25-ty}{$-$0.020}
1860
+ \mset{pd-k1b-m5b25-ty-k}{2/10}
1861
+ \mset{pd-k1b-m5b25-ty-p}{0.014}
1862
+ \mset{pd-k1b-m5b25-yt}{$-$0.004}
1863
+ \mset{pd-k1b-m5b25-yt-k}{4/10}
1864
+ \mset{pd-k1b-m5b25-yt-p}{0.188}
1865
+ \mset{pd-k1s-m5s25-yy}{$-$0.023}
1866
+ \mset{pd-k1s-m5s25-yy-k}{3/10}
1867
+ \mset{pd-k1s-m5s25-yy-p}{0.024}
1868
+ \mset{pd-k1s-m5s25-tt}{$-$0.017}
1869
+ \mset{pd-k1s-m5s25-tt-k}{2/10}
1870
+ \mset{pd-k1s-m5s25-tt-p}{0.014}
1871
+ \mset{pd-k1s-m5s25-ty}{$-$0.005}
1872
+ \mset{pd-k1s-m5s25-ty-k}{4/10}
1873
+ \mset{pd-k1s-m5s25-ty-p}{0.246}
1874
+ \mset{pd-k1s-m5s25-yt}{$-$0.035}
1875
+ \mset{pd-k1s-m5s25-yt-k}{0/10}
1876
+ \mset{pd-k1s-m5s25-yt-p}{0.001}
1877
+ \mset{pd-k4b-k1b-yy}{$-$0.023}
1878
+ \mset{pd-k4b-k1b-yy-k}{2/10}
1879
+ \mset{pd-k4b-k1b-yy-p}{0.006}
1880
+ \mset{pd-k4b-k1b-tt}{+0.006}
1881
+ \mset{pd-k4b-k1b-tt-k}{5/10}
1882
+ \mset{pd-k4b-k1b-tt-p}{0.278}
1883
+ \mset{pd-k4b-k1b-ty}{$-$0.003}
1884
+ \mset{pd-k4b-k1b-ty-k}{3/10}
1885
+ \mset{pd-k4b-k1b-ty-p}{0.455}
1886
+ \mset{pd-k4b-k1b-yt}{+0.015}
1887
+ \mset{pd-k4b-k1b-yt-k}{10/10}
1888
+ \mset{pd-k4b-k1b-yt-p}{0.001}
1889
+ \mset{pd-k4s-k1s-yy}{+0.017}
1890
+ \mset{pd-k4s-k1s-yy-k}{8/10}
1891
+ \mset{pd-k4s-k1s-yy-p}{0.024}
1892
+ \mset{pd-k4s-k1s-tt}{$-$0.010}
1893
+ \mset{pd-k4s-k1s-tt-k}{2/10}
1894
+ \mset{pd-k4s-k1s-tt-p}{0.042}
1895
+ \mset{pd-k4s-k1s-ty}{$-$0.001}
1896
+ \mset{pd-k4s-k1s-ty-k}{5/10}
1897
+ \mset{pd-k4s-k1s-ty-p}{0.500}
1898
+ \mset{pd-k4s-k1s-yt}{+0.017}
1899
+ \mset{pd-k4s-k1s-yt-k}{9/10}
1900
+ \mset{pd-k4s-k1s-yt-p}{0.002}
1901
+ \mset{pd-m5b50-m5b25-yy}{$-$0.005}
1902
+ \mset{pd-m5b50-m5b25-yy-k}{5/10}
1903
+ \mset{pd-m5b50-m5b25-yy-p}{0.312}
1904
+ \mset{pd-m5b50-m5b25-tt}{+0.013}
1905
+ \mset{pd-m5b50-m5b25-tt-k}{8/10}
1906
+ \mset{pd-m5b50-m5b25-tt-p}{0.065}
1907
+ \mset{pd-m5b50-m5b25-ty}{+0.009}
1908
+ \mset{pd-m5b50-m5b25-ty-k}{8/10}
1909
+ \mset{pd-m5b50-m5b25-ty-p}{0.019}
1910
+ \mset{pd-m5b50-m5b25-yt}{+0.015}
1911
+ \mset{pd-m5b50-m5b25-yt-k}{10/10}
1912
+ \mset{pd-m5b50-m5b25-yt-p}{0.001}
1913
+ \mset{pd-m5b75-m5b50-yy}{+0.012}
1914
+ \mset{pd-m5b75-m5b50-yy-k}{8/10}
1915
+ \mset{pd-m5b75-m5b50-yy-p}{0.014}
1916
+ \mset{pd-m5b75-m5b50-tt}{$-$0.003}
1917
+ \mset{pd-m5b75-m5b50-tt-k}{5/10}
1918
+ \mset{pd-m5b75-m5b50-tt-p}{0.312}
1919
+ \mset{pd-m5b75-m5b50-ty}{$-$0.043}
1920
+ \mset{pd-m5b75-m5b50-ty-k}{0/10}
1921
+ \mset{pd-m5b75-m5b50-ty-p}{0.001}
1922
+ \mset{pd-m5b75-m5b50-yt}{+0.001}
1923
+ \mset{pd-m5b75-m5b50-yt-k}{5/10}
1924
+ \mset{pd-m5b75-m5b50-yt-p}{0.348}
1925
+ \mset{pd-m6cs-m5s25-yy}{$-$0.039}
1926
+ \mset{pd-m6cs-m5s25-yy-k}{1/10}
1927
+ \mset{pd-m6cs-m5s25-yy-p}{0.002}
1928
+ \mset{pd-m6cs-m5s25-tt}{$-$0.019}
1929
+ \mset{pd-m6cs-m5s25-tt-k}{2/10}
1930
+ \mset{pd-m6cs-m5s25-tt-p}{0.010}
1931
+ \mset{pd-m6cs-m5s25-ty}{+0.004}
1932
+ \mset{pd-m6cs-m5s25-ty-k}{6/10}
1933
+ \mset{pd-m6cs-m5s25-ty-p}{0.216}
1934
+ \mset{pd-m6cs-m5s25-yt}{+0.004}
1935
+ \mset{pd-m6cs-m5s25-yt-k}{7/10}
1936
+ \mset{pd-m6cs-m5s25-yt-p}{0.116}
1937
+ \mset{pd-m6cb-m5b25-yy}{$-$0.032}
1938
+ \mset{pd-m6cb-m5b25-yy-k}{1/10}
1939
+ \mset{pd-m6cb-m5b25-yy-p}{0.003}
1940
+ \mset{pd-m6cb-m5b25-tt}{$-$0.004}
1941
+ \mset{pd-m6cb-m5b25-tt-k}{4/10}
1942
+ \mset{pd-m6cb-m5b25-tt-p}{0.097}
1943
+ \mset{pd-m6cb-m5b25-ty}{$-$0.005}
1944
+ \mset{pd-m6cb-m5b25-ty-k}{5/10}
1945
+ \mset{pd-m6cb-m5b25-ty-p}{0.188}
1946
+ \mset{pd-m6cb-m5b25-yt}{+0.014}
1947
+ \mset{pd-m6cb-m5b25-yt-k}{10/10}
1948
+ \mset{pd-m6cb-m5b25-yt-p}{0.001}
1949
+ \mset{pd-m6cb50-m6cb-yy}{+0.005}
1950
+ \mset{pd-m6cb50-m6cb-yy-k}{6/10}
1951
+ \mset{pd-m6cb50-m6cb-yy-p}{0.278}
1952
+ \mset{pd-m6cb50-m6cb-tt}{+0.016}
1953
+ \mset{pd-m6cb50-m6cb-tt-k}{8/10}
1954
+ \mset{pd-m6cb50-m6cb-tt-p}{0.005}
1955
+ \mset{pd-m6cb50-m6cb-ty}{$-$0.020}
1956
+ \mset{pd-m6cb50-m6cb-ty-k}{1/10}
1957
+ \mset{pd-m6cb50-m6cb-ty-p}{0.005}
1958
+ \mset{pd-m6cb50-m6cb-yt}{$-$0.011}
1959
+ \mset{pd-m6cb50-m6cb-yt-k}{1/10}
1960
+ \mset{pd-m6cb50-m6cb-yt-p}{0.003}
1961
+ \mset{pd-m6cw2s-m6cs-yy}{+0.006}
1962
+ \mset{pd-m6cw2s-m6cs-yy-k}{7/10}
1963
+ \mset{pd-m6cw2s-m6cs-yy-p}{0.097}
1964
+ \mset{pd-m6cw2s-m6cs-tt}{$-$0.001}
1965
+ \mset{pd-m6cw2s-m6cs-tt-k}{5/10}
1966
+ \mset{pd-m6cw2s-m6cs-tt-p}{0.423}
1967
+ \mset{pd-m6cw2s-m6cs-ty}{$-$0.012}
1968
+ \mset{pd-m6cw2s-m6cs-ty-k}{3/10}
1969
+ \mset{pd-m6cw2s-m6cs-ty-p}{0.097}
1970
+ \mset{pd-m6cw2s-m6cs-yt}{$-$0.002}
1971
+ \mset{pd-m6cw2s-m6cs-yt-k}{2/10}
1972
+ \mset{pd-m6cw2s-m6cs-yt-p}{0.053}
1973
+ \mset{pd-m6cw2b-m6cb-yy}{+0.009}
1974
+ \mset{pd-m6cw2b-m6cb-yy-k}{6/10}
1975
+ \mset{pd-m6cw2b-m6cb-yy-p}{0.216}
1976
+ \mset{pd-m6cw2b-m6cb-tt}{$-$0.016}
1977
+ \mset{pd-m6cw2b-m6cb-tt-k}{2/10}
1978
+ \mset{pd-m6cw2b-m6cb-tt-p}{0.019}
1979
+ \mset{pd-m6cw2b-m6cb-ty}{+0.003}
1980
+ \mset{pd-m6cw2b-m6cb-ty-k}{6/10}
1981
+ \mset{pd-m6cw2b-m6cb-ty-p}{0.348}
1982
+ \mset{pd-m6cw2b-m6cb-yt}{+0.000}
1983
+ \mset{pd-m6cw2b-m6cb-yt-k}{5/10}
1984
+ \mset{pd-m6cw2b-m6cb-yt-p}{0.500}
1985
+ \mset{pd-m6ds-m5s25-yy}{$-$0.009}
1986
+ \mset{pd-m6ds-m5s25-yy-k}{4/10}
1987
+ \mset{pd-m6ds-m5s25-yy-p}{0.188}
1988
+ \mset{pd-m6ds-m5s25-tt}{$-$0.025}
1989
+ \mset{pd-m6ds-m5s25-tt-k}{1/10}
1990
+ \mset{pd-m6ds-m5s25-tt-p}{0.003}
1991
+ \mset{pd-m6ds-m5s25-ty}{+0.008}
1992
+ \mset{pd-m6ds-m5s25-ty-k}{7/10}
1993
+ \mset{pd-m6ds-m5s25-ty-p}{0.138}
1994
+ \mset{pd-m6ds-m5s25-yt}{+0.012}
1995
+ \mset{pd-m6ds-m5s25-yt-k}{10/10}
1996
+ \mset{pd-m6ds-m5s25-yt-p}{0.001}
1997
+ \mset{pd-m6ds-m6cs-yy}{+0.029}
1998
+ \mset{pd-m6ds-m6cs-yy-k}{8/10}
1999
+ \mset{pd-m6ds-m6cs-yy-p}{0.005}
2000
+ \mset{pd-m6ds-m6cs-tt}{$-$0.006}
2001
+ \mset{pd-m6ds-m6cs-tt-k}{3/10}
2002
+ \mset{pd-m6ds-m6cs-tt-p}{0.138}
2003
+ \mset{pd-m6ds-m6cs-ty}{+0.004}
2004
+ \mset{pd-m6ds-m6cs-ty-k}{6/10}
2005
+ \mset{pd-m6ds-m6cs-ty-p}{0.312}
2006
+ \mset{pd-m6ds-m6cs-yt}{+0.008}
2007
+ \mset{pd-m6ds-m6cs-yt-k}{8/10}
2008
+ \mset{pd-m6ds-m6cs-yt-p}{0.023}
2009
+ \mset{pd-m6db-m5b25-yy}{$-$0.008}
2010
+ \mset{pd-m6db-m5b25-yy-k}{3/10}
2011
+ \mset{pd-m6db-m5b25-yy-p}{0.138}
2012
+ \mset{pd-m6db-m5b25-tt}{+0.008}
2013
+ \mset{pd-m6db-m5b25-tt-k}{7/10}
2014
+ \mset{pd-m6db-m5b25-tt-p}{0.065}
2015
+ \mset{pd-m6db-m5b25-ty}{+0.001}
2016
+ \mset{pd-m6db-m5b25-ty-k}{6/10}
2017
+ \mset{pd-m6db-m5b25-ty-p}{0.461}
2018
+ \mset{pd-m6db-m5b25-yt}{+0.012}
2019
+ \mset{pd-m6db-m5b25-yt-k}{8/10}
2020
+ \mset{pd-m6db-m5b25-yt-p}{0.005}
2021
+ \mset{pd-m6db-m6cb-yy}{+0.024}
2022
+ \mset{pd-m6db-m6cb-yy-k}{8/10}
2023
+ \mset{pd-m6db-m6cb-yy-p}{0.005}
2024
+ \mset{pd-m6db-m6cb-tt}{+0.012}
2025
+ \mset{pd-m6db-m6cb-tt-k}{8/10}
2026
+ \mset{pd-m6db-m6cb-tt-p}{0.024}
2027
+ \mset{pd-m6db-m6cb-ty}{+0.006}
2028
+ \mset{pd-m6db-m6cb-ty-k}{6/10}
2029
+ \mset{pd-m6db-m6cb-ty-p}{0.138}
2030
+ \mset{pd-m6db-m6cb-yt}{$-$0.002}
2031
+ \mset{pd-m6db-m6cb-yt-k}{6/10}
2032
+ \mset{pd-m6db-m6cb-yt-p}{0.312}
2033
+ \mset{pd-m6ec-m6ef-yy}{+0.016}
2034
+ \mset{pd-m6ec-m6ef-yy-k}{9/10}
2035
+ \mset{pd-m6ec-m6ef-yy-p}{0.007}
2036
+ \mset{pd-m6ec-m6ef-tt}{+0.015}
2037
+ \mset{pd-m6ec-m6ef-tt-k}{7/10}
2038
+ \mset{pd-m6ec-m6ef-tt-p}{0.080}
2039
+ \mset{pd-m6ec-m6ef-ty}{$-$0.004}
2040
+ \mset{pd-m6ec-m6ef-ty-k}{6/10}
2041
+ \mset{pd-m6ec-m6ef-ty-p}{0.539}
2042
+ \mset{pd-m6ec-m6ef-yt}{+0.013}
2043
+ \mset{pd-m6ec-m6ef-yt-k}{9/10}
2044
+ \mset{pd-m6ec-m6ef-yt-p}{0.002}
2045
+ \mset{pd-v4s-m6ds-yy}{$-$0.045}
2046
+ \mset{pd-v4s-m6ds-yy-k}{0/10}
2047
+ \mset{pd-v4s-m6ds-yy-p}{0.001}
2048
+ \mset{pd-v4s-m6ds-tt}{+0.009}
2049
+ \mset{pd-v4s-m6ds-tt-k}{6/10}
2050
+ \mset{pd-v4s-m6ds-tt-p}{0.097}
2051
+ \mset{pd-v4s-m6ds-ty}{+0.007}
2052
+ \mset{pd-v4s-m6ds-ty-k}{7/10}
2053
+ \mset{pd-v4s-m6ds-ty-p}{0.097}
2054
+ \mset{pd-v4s-m6ds-yt}{$-$0.007}
2055
+ \mset{pd-v4s-m6ds-yt-k}{1/10}
2056
+ \mset{pd-v4s-m6ds-yt-p}{0.003}
2057
+ \mset{pd-v4b-m6db-yy}{+0.017}
2058
+ \mset{pd-v4b-m6db-yy-k}{9/10}
2059
+ \mset{pd-v4b-m6db-yy-p}{0.007}
2060
+ \mset{pd-v4b-m6db-tt}{$-$0.007}
2061
+ \mset{pd-v4b-m6db-tt-k}{4/10}
2062
+ \mset{pd-v4b-m6db-tt-p}{0.216}
2063
+ \mset{pd-v4b-m6db-ty}{$-$0.017}
2064
+ \mset{pd-v4b-m6db-ty-k}{3/10}
2065
+ \mset{pd-v4b-m6db-ty-p}{0.053}
2066
+ \mset{pd-v4b-m6db-yt}{+0.003}
2067
+ \mset{pd-v4b-m6db-yt-k}{8/10}
2068
+ \mset{pd-v4b-m6db-yt-p}{0.080}
2069
+ \mset{pd-phikon-m6ds-yy}{+0.024}
2070
+ \mset{pd-phikon-m6ds-yy-k}{9/10}
2071
+ \mset{pd-phikon-m6ds-yy-p}{0.002}
2072
+ \mset{pd-phikon-m6ds-tt}{$-$0.001}
2073
+ \mset{pd-phikon-m6ds-tt-k}{4/10}
2074
+ \mset{pd-phikon-m6ds-tt-p}{0.500}
2075
+ \mset{pd-phikon-m6ds-ty}{+0.041}
2076
+ \mset{pd-phikon-m6ds-ty-k}{9/10}
2077
+ \mset{pd-phikon-m6ds-ty-p}{0.002}
2078
+ \mset{pd-phikon-m6ds-yt}{+0.025}
2079
+ \mset{pd-phikon-m6ds-yt-k}{10/10}
2080
+ \mset{pd-phikon-m6ds-yt-p}{0.001}
2081
+ \mset{pd-phikon-m6db-yy}{+0.043}
2082
+ \mset{pd-phikon-m6db-yy-k}{10/10}
2083
+ \mset{pd-phikon-m6db-yy-p}{0.001}
2084
+ \mset{pd-phikon-m6db-tt}{$-$0.014}
2085
+ \mset{pd-phikon-m6db-tt-k}{1/10}
2086
+ \mset{pd-phikon-m6db-tt-p}{0.007}
2087
+ \mset{pd-phikon-m6db-ty}{+0.036}
2088
+ \mset{pd-phikon-m6db-ty-k}{9/10}
2089
+ \mset{pd-phikon-m6db-ty-p}{0.002}
2090
+ \mset{pd-phikon-m6db-yt}{+0.026}
2091
+ \mset{pd-phikon-m6db-yt-k}{10/10}
2092
+ \mset{pd-phikon-m6db-yt-p}{0.001}
2093
+ \mset{pd-phikon-v4s-yy}{+0.069}
2094
+ \mset{pd-phikon-v4s-yy-k}{10/10}
2095
+ \mset{pd-phikon-v4s-yy-p}{0.001}
2096
+ \mset{pd-phikon-v4s-tt}{$-$0.010}
2097
+ \mset{pd-phikon-v4s-tt-k}{2/10}
2098
+ \mset{pd-phikon-v4s-tt-p}{0.161}
2099
+ \mset{pd-phikon-v4s-ty}{+0.034}
2100
+ \mset{pd-phikon-v4s-ty-k}{10/10}
2101
+ \mset{pd-phikon-v4s-ty-p}{0.001}
2102
+ \mset{pd-phikon-v4s-yt}{+0.033}
2103
+ \mset{pd-phikon-v4s-yt-k}{10/10}
2104
+ \mset{pd-phikon-v4s-yt-p}{0.001}
2105
+ \mset{pd-phikon-v4b-yy}{+0.027}
2106
+ \mset{pd-phikon-v4b-yy-k}{10/10}
2107
+ \mset{pd-phikon-v4b-yy-p}{0.001}
2108
+ \mset{pd-phikon-v4b-tt}{$-$0.008}
2109
+ \mset{pd-phikon-v4b-tt-k}{3/10}
2110
+ \mset{pd-phikon-v4b-tt-p}{0.116}
2111
+ \mset{pd-phikon-v4b-ty}{+0.053}
2112
+ \mset{pd-phikon-v4b-ty-k}{9/10}
2113
+ \mset{pd-phikon-v4b-ty-p}{0.002}
2114
+ \mset{pd-phikon-v4b-yt}{+0.023}
2115
+ \mset{pd-phikon-v4b-yt-k}{10/10}
2116
+ \mset{pd-phikon-v4b-yt-p}{0.001}
2117
+ \mset{pd-v4so1-v4s-yy}{+0.012}
2118
+ \mset{pd-v4so1-v4s-yy-k}{8/10}
2119
+ \mset{pd-v4so1-v4s-yy-p}{0.065}
2120
+ \mset{pd-v4so1-v4s-tt}{$-$0.008}
2121
+ \mset{pd-v4so1-v4s-tt-k}{4/10}
2122
+ \mset{pd-v4so1-v4s-tt-p}{0.097}
2123
+ \mset{pd-v4so1-v4s-ty}{$-$0.039}
2124
+ \mset{pd-v4so1-v4s-ty-k}{0/10}
2125
+ \mset{pd-v4so1-v4s-ty-p}{0.001}
2126
+ \mset{pd-v4so1-v4s-yt}{$-$0.001}
2127
+ \mset{pd-v4so1-v4s-yt-k}{5/10}
2128
+ \mset{pd-v4so1-v4s-yt-p}{0.615}
2129
+ \mset{pd-v5s-v4s-yy}{+0.004}
2130
+ \mset{pd-v5s-v4s-yy-k}{7/10}
2131
+ \mset{pd-v5s-v4s-yy-p}{0.216}
2132
+ \mset{pd-v5s-v4s-tt}{+0.001}
2133
+ \mset{pd-v5s-v4s-tt-k}{4/10}
2134
+ \mset{pd-v5s-v4s-tt-p}{0.577}
2135
+ \mset{pd-v5s-v4s-ty}{$-$0.024}
2136
+ \mset{pd-v5s-v4s-ty-k}{0/10}
2137
+ \mset{pd-v5s-v4s-ty-p}{0.001}
2138
+ \mset{pd-v5s-v4s-yt}{$-$0.009}
2139
+ \mset{pd-v5s-v4s-yt-k}{1/10}
2140
+ \mset{pd-v5s-v4s-yt-p}{0.019}
2141
+ \mset{pd-v5b-v4b-yy}{$-$0.013}
2142
+ \mset{pd-v5b-v4b-yy-k}{3/10}
2143
+ \mset{pd-v5b-v4b-yy-p}{0.053}
2144
+ \mset{pd-v5b-v4b-tt}{+0.014}
2145
+ \mset{pd-v5b-v4b-tt-k}{7/10}
2146
+ \mset{pd-v5b-v4b-tt-p}{0.019}
2147
+ \mset{pd-v5b-v4b-ty}{$-$0.004}
2148
+ \mset{pd-v5b-v4b-ty-k}{5/10}
2149
+ \mset{pd-v5b-v4b-ty-p}{0.385}
2150
+ \mset{pd-v5b-v4b-yt}{$-$0.001}
2151
+ \mset{pd-v5b-v4b-yt-k}{4/10}
2152
+ \mset{pd-v5b-v4b-yt-p}{0.246}
2153
+ \mset{pd-jms3-m6ds-yy}{$-$0.016}
2154
+ \mset{pd-jms3-m6ds-yy-k}{1/10}
2155
+ \mset{pd-jms3-m6ds-yy-p}{0.014}
2156
+ \mset{pd-jms3-m6ds-tt}{$-$0.001}
2157
+ \mset{pd-jms3-m6ds-tt-k}{7/10}
2158
+ \mset{pd-jms3-m6ds-tt-p}{0.722}
2159
+ \mset{pd-jms3-m6ds-ty}{+0.027}
2160
+ \mset{pd-jms3-m6ds-ty-k}{9/10}
2161
+ \mset{pd-jms3-m6ds-ty-p}{0.003}
2162
+ \mset{pd-jms3-m6ds-yt}{+0.010}
2163
+ \mset{pd-jms3-m6ds-yt-k}{8/10}
2164
+ \mset{pd-jms3-m6ds-yt-p}{0.005}
2165
+ \mset{pd-jms4-m6ds-yy}{$-$0.022}
2166
+ \mset{pd-jms4-m6ds-yy-k}{0/10}
2167
+ \mset{pd-jms4-m6ds-yy-p}{0.001}
2168
+ \mset{pd-jms4-m6ds-tt}{$-$0.002}
2169
+ \mset{pd-jms4-m6ds-tt-k}{5/10}
2170
+ \mset{pd-jms4-m6ds-tt-p}{0.348}
2171
+ \mset{pd-jms4-m6ds-ty}{+0.026}
2172
+ \mset{pd-jms4-m6ds-ty-k}{10/10}
2173
+ \mset{pd-jms4-m6ds-ty-p}{0.001}
2174
+ \mset{pd-jms4-m6ds-yt}{+0.008}
2175
+ \mset{pd-jms4-m6ds-yt-k}{7/10}
2176
+ \mset{pd-jms4-m6ds-yt-p}{0.032}
2177
+ \mset{pd-jms3k2-m6ds-yy}{$-$0.008}
2178
+ \mset{pd-jms3k2-m6ds-yy-k}{4/10}
2179
+ \mset{pd-jms3k2-m6ds-yy-p}{0.080}
2180
+ \mset{pd-jms3k2-m6ds-tt}{$-$0.000}
2181
+ \mset{pd-jms3k2-m6ds-tt-k}{5/10}
2182
+ \mset{pd-jms3k2-m6ds-tt-p}{0.461}
2183
+ \mset{pd-jms3k2-m6ds-ty}{+0.025}
2184
+ \mset{pd-jms3k2-m6ds-ty-k}{10/10}
2185
+ \mset{pd-jms3k2-m6ds-ty-p}{0.001}
2186
+ \mset{pd-jms3k2-m6ds-yt}{+0.016}
2187
+ \mset{pd-jms3k2-m6ds-yt-k}{10/10}
2188
+ \mset{pd-jms3k2-m6ds-yt-p}{0.001}
2189
+ \mset{pd-jms4k2-m6ds-yy}{$-$0.013}
2190
+ \mset{pd-jms4k2-m6ds-yy-k}{3/10}
2191
+ \mset{pd-jms4k2-m6ds-yy-p}{0.013}
2192
+ \mset{pd-jms4k2-m6ds-tt}{$-$0.001}
2193
+ \mset{pd-jms4k2-m6ds-tt-k}{5/10}
2194
+ \mset{pd-jms4k2-m6ds-tt-p}{0.461}
2195
+ \mset{pd-jms4k2-m6ds-ty}{+0.020}
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+ \mset{pd-e9995s4-jj25s3-tt-p}{0.007}
2747
+ \mset{pd-e9995s4-jj25s3-ty}{$-$0.011}
2748
+ \mset{pd-e9995s4-jj25s3-ty-k}{2/10}
2749
+ \mset{pd-e9995s4-jj25s3-ty-p}{0.097}
2750
+ \mset{pd-e9995s4-jj25s3-yt}{$-$0.002}
2751
+ \mset{pd-e9995s4-jj25s3-yt-k}{4/10}
2752
+ \mset{pd-e9995s4-jj25s3-yt-p}{0.278}
2753
+ \mset{pd-e999l-jj25s3-yy}{+0.009}
2754
+ \mset{pd-e999l-jj25s3-yy-k}{6/10}
2755
+ \mset{pd-e999l-jj25s3-yy-p}{0.188}
2756
+ \mset{pd-e999l-jj25s3-tt}{$-$0.030}
2757
+ \mset{pd-e999l-jj25s3-tt-k}{0/10}
2758
+ \mset{pd-e999l-jj25s3-tt-p}{0.001}
2759
+ \mset{pd-e999l-jj25s3-ty}{$-$0.000}
2760
+ \mset{pd-e999l-jj25s3-ty-k}{5/10}
2761
+ \mset{pd-e999l-jj25s3-ty-p}{0.423}
2762
+ \mset{pd-e999l-jj25s3-yt}{$-$0.015}
2763
+ \mset{pd-e999l-jj25s3-yt-k}{0/10}
2764
+ \mset{pd-e999l-jj25s3-yt-p}{0.001}
2765
+ \mset{pd-e999s5-jj25s3-yy}{+0.015}
2766
+ \mset{pd-e999s5-jj25s3-yy-k}{7/10}
2767
+ \mset{pd-e999s5-jj25s3-yy-p}{0.065}
2768
+ \mset{pd-e999s5-jj25s3-tt}{$-$0.029}
2769
+ \mset{pd-e999s5-jj25s3-tt-k}{0/10}
2770
+ \mset{pd-e999s5-jj25s3-tt-p}{0.001}
2771
+ \mset{pd-e999s5-jj25s3-ty}{$-$0.013}
2772
+ \mset{pd-e999s5-jj25s3-ty-k}{2/10}
2773
+ \mset{pd-e999s5-jj25s3-ty-p}{0.007}
2774
+ \mset{pd-e999s5-jj25s3-yt}{$-$0.008}
2775
+ \mset{pd-e999s5-jj25s3-yt-k}{3/10}
2776
+ \mset{pd-e999s5-jj25s3-yt-p}{0.024}
2777
+ \mset{pd-e999s6-jj25s3-yy}{+0.013}
2778
+ \mset{pd-e999s6-jj25s3-yy-k}{7/10}
2779
+ \mset{pd-e999s6-jj25s3-yy-p}{0.032}
2780
+ \mset{pd-e999s6-jj25s3-tt}{$-$0.032}
2781
+ \mset{pd-e999s6-jj25s3-tt-k}{0/10}
2782
+ \mset{pd-e999s6-jj25s3-tt-p}{0.001}
2783
+ \mset{pd-e999s6-jj25s3-ty}{$-$0.001}
2784
+ \mset{pd-e999s6-jj25s3-ty-k}{4/10}
2785
+ \mset{pd-e999s6-jj25s3-ty-p}{0.423}
2786
+ \mset{pd-e999s6-jj25s3-yt}{$-$0.010}
2787
+ \mset{pd-e999s6-jj25s3-yt-k}{1/10}
2788
+ \mset{pd-e999s6-jj25s3-yt-p}{0.003}
2789
+ \mset{pd-mixa75-jj25s3-yy}{+0.003}
2790
+ \mset{pd-mixa75-jj25s3-yy-k}{7/10}
2791
+ \mset{pd-mixa75-jj25s3-yy-p}{0.216}
2792
+ \mset{pd-mixa75-jj25s3-tt}{$-$0.013}
2793
+ \mset{pd-mixa75-jj25s3-tt-k}{2/10}
2794
+ \mset{pd-mixa75-jj25s3-tt-p}{0.014}
2795
+ \mset{pd-mixa75-jj25s3-ty}{$-$0.018}
2796
+ \mset{pd-mixa75-jj25s3-ty-k}{2/10}
2797
+ \mset{pd-mixa75-jj25s3-ty-p}{0.024}
2798
+ \mset{pd-mixa75-jj25s3-yt}{+0.002}
2799
+ \mset{pd-mixa75-jj25s3-yt-k}{6/10}
2800
+ \mset{pd-mixa75-jj25s3-yt-p}{0.238}
2801
+ \mset{pd-mixa50-jj25s3-yy}{+0.002}
2802
+ \mset{pd-mixa50-jj25s3-yy-k}{6/10}
2803
+ \mset{pd-mixa50-jj25s3-yy-p}{0.423}
2804
+ \mset{pd-mixa50-jj25s3-tt}{$-$0.022}
2805
+ \mset{pd-mixa50-jj25s3-tt-k}{1/10}
2806
+ \mset{pd-mixa50-jj25s3-tt-p}{0.002}
2807
+ \mset{pd-mixa50-jj25s3-ty}{$-$0.017}
2808
+ \mset{pd-mixa50-jj25s3-ty-k}{2/10}
2809
+ \mset{pd-mixa50-jj25s3-ty-p}{0.042}
2810
+ \mset{pd-mixa50-jj25s3-yt}{$-$0.003}
2811
+ \mset{pd-mixa50-jj25s3-yt-k}{4/10}
2812
+ \mset{pd-mixa50-jj25s3-yt-p}{0.138}
2813
+ \mset{pd-xtf-jj25s3-yy}{$-$0.002}
2814
+ \mset{pd-xtf-jj25s3-yy-k}{4/10}
2815
+ \mset{pd-xtf-jj25s3-yy-p}{0.385}
2816
+ \mset{pd-xtf-jj25s3-tt}{$-$0.026}
2817
+ \mset{pd-xtf-jj25s3-tt-k}{2/10}
2818
+ \mset{pd-xtf-jj25s3-tt-p}{0.005}
2819
+ \mset{pd-xtf-jj25s3-ty}{$-$0.009}
2820
+ \mset{pd-xtf-jj25s3-ty-k}{2/10}
2821
+ \mset{pd-xtf-jj25s3-ty-p}{0.065}
2822
+ \mset{pd-xtf-jj25s3-yt}{$-$0.008}
2823
+ \mset{pd-xtf-jj25s3-yt-k}{1/10}
2824
+ \mset{pd-xtf-jj25s3-yt-p}{0.005}
2825
+ \mset{pd-xth-jj25s3-yy}{$-$0.000}
2826
+ \mset{pd-xth-jj25s3-yy-k}{3/10}
2827
+ \mset{pd-xth-jj25s3-yy-p}{0.385}
2828
+ \mset{pd-xth-jj25s3-tt}{$-$0.038}
2829
+ \mset{pd-xth-jj25s3-tt-k}{0/10}
2830
+ \mset{pd-xth-jj25s3-tt-p}{0.001}
2831
+ \mset{pd-xth-jj25s3-ty}{$-$0.019}
2832
+ \mset{pd-xth-jj25s3-ty-k}{2/10}
2833
+ \mset{pd-xth-jj25s3-ty-p}{0.080}
2834
+ \mset{pd-xth-jj25s3-yt}{$-$0.012}
2835
+ \mset{pd-xth-jj25s3-yt-k}{1/10}
2836
+ \mset{pd-xth-jj25s3-yt-p}{0.002}
2837
+ \mset{pd-wisea75-jj25s3-yy}{+0.011}
2838
+ \mset{pd-wisea75-jj25s3-yy-k}{7/10}
2839
+ \mset{pd-wisea75-jj25s3-yy-p}{0.116}
2840
+ \mset{pd-wisea75-jj25s3-tt}{$-$0.003}
2841
+ \mset{pd-wisea75-jj25s3-tt-k}{3/10}
2842
+ \mset{pd-wisea75-jj25s3-tt-p}{0.246}
2843
+ \mset{pd-wisea75-jj25s3-ty}{$-$0.011}
2844
+ \mset{pd-wisea75-jj25s3-ty-k}{2/10}
2845
+ \mset{pd-wisea75-jj25s3-ty-p}{0.065}
2846
+ \mset{pd-wisea75-jj25s3-yt}{$-$0.003}
2847
+ \mset{pd-wisea75-jj25s3-yt-k}{3/10}
2848
+ \mset{pd-wisea75-jj25s3-yt-p}{0.097}
2849
+ \mset{pd-wisea50-jj25s3-yy}{+0.015}
2850
+ \mset{pd-wisea50-jj25s3-yy-k}{6/10}
2851
+ \mset{pd-wisea50-jj25s3-yy-p}{0.084}
2852
+ \mset{pd-wisea50-jj25s3-tt}{+0.003}
2853
+ \mset{pd-wisea50-jj25s3-tt-k}{6/10}
2854
+ \mset{pd-wisea50-jj25s3-tt-p}{0.348}
2855
+ \mset{pd-wisea50-jj25s3-ty}{$-$0.015}
2856
+ \mset{pd-wisea50-jj25s3-ty-k}{2/10}
2857
+ \mset{pd-wisea50-jj25s3-ty-p}{0.019}
2858
+ \mset{pd-wisea50-jj25s3-yt}{$-$0.004}
2859
+ \mset{pd-wisea50-jj25s3-yt-k}{3/10}
2860
+ \mset{pd-wisea50-jj25s3-yt-p}{0.065}
2861
+ \mset{pd-wisea75-m5s25-yy}{$-$0.003}
2862
+ \mset{pd-wisea75-m5s25-yy-k}{4/10}
2863
+ \mset{pd-wisea75-m5s25-yy-p}{0.278}
2864
+ \mset{pd-wisea75-m5s25-tt}{$-$0.017}
2865
+ \mset{pd-wisea75-m5s25-tt-k}{1/10}
2866
+ \mset{pd-wisea75-m5s25-tt-p}{0.005}
2867
+ \mset{pd-wisea75-m5s25-ty}{+0.038}
2868
+ \mset{pd-wisea75-m5s25-ty-k}{10/10}
2869
+ \mset{pd-wisea75-m5s25-ty-p}{0.001}
2870
+ \mset{pd-wisea75-m5s25-yt}{+0.022}
2871
+ \mset{pd-wisea75-m5s25-yt-k}{10/10}
2872
+ \mset{pd-wisea75-m5s25-yt-p}{0.001}
2873
+ \mset{pd-wisea50-m5s25-yy}{+0.002}
2874
+ \mset{pd-wisea50-m5s25-yy-k}{6/10}
2875
+ \mset{pd-wisea50-m5s25-yy-p}{0.539}
2876
+ \mset{pd-wisea50-m5s25-tt}{$-$0.012}
2877
+ \mset{pd-wisea50-m5s25-tt-k}{2/10}
2878
+ \mset{pd-wisea50-m5s25-tt-p}{0.042}
2879
+ \mset{pd-wisea50-m5s25-ty}{+0.035}
2880
+ \mset{pd-wisea50-m5s25-ty-k}{10/10}
2881
+ \mset{pd-wisea50-m5s25-ty-p}{0.001}
2882
+ \mset{pd-wisea50-m5s25-yt}{+0.020}
2883
+ \mset{pd-wisea50-m5s25-yt-k}{10/10}
2884
+ \mset{pd-wisea50-m5s25-yt-p}{0.001}
2885
+ \mset{best-yy}{0.871}
2886
+ \mset{best-yy-gap}{$-$0.002}
2887
+ \mset{best-yy-who}{JEPA round 2 on the 50k start}
2888
+ \mset{best-tt}{0.705}
2889
+ \mset{best-tt-gap}{+0.026}
2890
+ \mset{best-tt-who}{M5.G ViT-S, 25k snapshot (main)}
2891
+ \mset{best-ty}{0.812}
2892
+ \mset{best-ty-gap}{+0.001}
2893
+ \mset{best-ty-who}{JEPA round 2, the chain from round 1 seed 4}
2894
+ \mset{best-yt}{0.656}
2895
+ \mset{best-yt-gap}{$-$0.006}
2896
+ \mset{best-yt-who}{JEPA from M6.D ViT-S, seed 4, step 2,000 (mid-schedule)}
data/paper/book-data/trackA_dot_budget-yale.dat ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ y group mean sd lo hi
2
+ 1 s16 0.8268 0.0484 0.6847 0.9397
3
+ 2 s16 0.8105 0.0260 0.6575 0.9331
data/paper/book-data/trackA_dot_budget-yale_rows.dat ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ y label
2
+ 1 ssl-vits16 final, 400 tiles
3
+ 2 p9final-all
data/paper/book-data/trackA_dot_eq-ish.dat ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ y group mean sd lo hi
2
+ 1 ref 0.7646 0.1067 0.5238 0.9639
3
+ 2 s16 0.6984 0.0721 0.4253 0.9396
4
+ 3 dst 0.6899 0.1029 0.4176 0.9363
5
+ 4 ref 0.6746 0.1186 0.4111 0.9183
data/paper/book-data/trackA_dot_eq-ish_rows.dat ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ y label
2
+ 1 H-optimus-0, card norm., CLS
3
+ 2 ssl-vits16 final (93k)
4
+ 3 D13: Midnight-12k teacher, 20k steps
5
+ 4 Midnight-12k, CLS
data/paper/book-data/trackA_dot_her2-tcga.dat ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y group mean sd lo hi
2
+ 1 ref 0.6694 0.0718 0.5518 0.7794
3
+ 2 ref 0.6655 0.0603 0.5463 0.7786
4
+ 3 dstb 0.6627 0.0615 0.5450 0.7749
5
+ 4 ref 0.6597 0.0722 0.5444 0.7702
6
+ 5 ref 0.6588 0.0578 0.5411 0.7751
7
+ 6 best 0.6578 0.0732 0.5416 0.7665
8
+ 7 ref 0.6563 0.0578 0.5370 0.7675
9
+ 8 dst 0.6532 0.0821 0.5349 0.7647
10
+ 9 dst 0.6512 0.0497 0.5315 0.7651
11
+ 10 dstb 0.6452 0.0643 0.5280 0.7548
12
+ 11 ref 0.6299 0.0484 0.5101 0.7440
13
+ 12 b16 0.6214 0.0686 0.4948 0.7370
14
+ 13 dst 0.6159 0.0404 0.4960 0.7301
15
+ 14 s16 0.6123 0.0664 0.4885 0.7281
16
+ 15 s16 0.6102 0.0557 0.4854 0.7308
17
+ 16 ref 0.6063 0.0340 0.4858 0.7240
18
+ 17 ref 0.6050 0.0478 0.4802 0.7244
19
+ 18 ref 0.6033 0.0543 0.4831 0.7219
20
+ 19 s16 0.5972 0.0696 0.4754 0.7143
21
+ 20 s16 0.5954 0.0515 0.4697 0.7116
22
+ 21 s16 0.5941 0.0610 0.4687 0.7109
23
+ 22 s16 0.5924 0.0495 0.4678 0.7107
24
+ 23 b16 0.5915 0.0503 0.4697 0.7101
25
+ 24 s16 0.5912 0.0467 0.4671 0.7125
26
+ 25 dst 0.5905 0.0794 0.4695 0.7067
27
+ 26 b16 0.5895 0.0613 0.4668 0.7071
28
+ 27 s16 0.5888 0.0358 0.4633 0.7083
29
+ 28 s16 0.5867 0.0490 0.4603 0.7057
30
+ 29 dst 0.5719 0.0435 0.4470 0.6916
31
+ 30 ctl 0.5670 0.0681 0.4442 0.6900
32
+ 31 dst 0.5601 0.0971 0.4381 0.6808
33
+ 32 dst 0.5578 0.0510 0.4343 0.6741
34
+ 33 s16 0.5432 0.0547 0.4156 0.6662
35
+ 34 ctl 0.5410 0.0813 0.4177 0.6604
36
+ 35 ctl 0.4849 0.0536 0.3597 0.6067
data/paper/book-data/trackA_dot_her2-tcga_rows.dat ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y label
2
+ 1 H-optimus-0, card norm., CLS+mean
3
+ 2 H-optimus-0, card norm., CLS, 1.0\,\textmu m/px
4
+ 3 \textbf{\textcolor{hrB16!80!black}{D18: H-optimus-0, ViT-B/16, 5k, from step 40k}}
5
+ 4 H-optimus-0, card norm., CLS
6
+ 5 H-optimus-0, ImageNet norm. (Aug.)
7
+ 6 \textbf{\textcolor{hrBest}{D16: H-optimus-0, 5k, from final}}
8
+ 7 Phikon v1, ViT-B/16 (Aug.)
9
+ 8 D14: H-optimus-0 teacher, 20k steps
10
+ 9 D16: H-optimus-0, 5k, from step 50k
11
+ 10 D18: H-optimus-0, ViT-B/16, 5k, from step 45k
12
+ 11 Midnight-12k, CLS+mean
13
+ 12 ssl-vitb16 step 40k
14
+ 13 D13: Midnight-12k teacher, 20k steps
15
+ 14 ssl-vits16 step 45k
16
+ 15 ssl-vits16 step 35k
17
+ 16 Midnight-12k, CLS
18
+ 17 Hibou-B (Aug.)
19
+ 18 Midnight-12k, CLS, 1.0\,\textmu m/px
20
+ 19 ssl-vits16 step 40k
21
+ 20 ssl-vits16 final (93k)
22
+ 21 ssl-vits16 step 65k
23
+ 22 ssl-vits16 step 60k
24
+ 23 ssl-vitb16 step 10k
25
+ 24 ssl-vits16 step 20k
26
+ 25 D16: H-optimus-0, 5k, from random
27
+ 26 ssl-vitb16 step 35k
28
+ 27 ssl-vits16 step 55k
29
+ 28 ssl-vits16 step 50k
30
+ 29 D15: Midnight, 5k, from step 50k
31
+ 30 ResNet-50, ImageNet (Aug.)
32
+ 31 D15: Midnight, 5k, from final
33
+ 32 D15: Midnight, 5k, from random
34
+ 33 ssl-vits16 step 5k
35
+ 34 DINOv2 ViT-S/14 (natural images)
36
+ 35 random weights, ViT-S/16
data/paper/book-data/trackA_dot_her2-yale.dat ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y group mean sd lo hi
2
+ 1 ref 0.9134 0.0673 0.8171 0.9801
3
+ 2 ref 0.9129 0.0614 0.8159 0.9797
4
+ 3 ref 0.9105 0.0575 0.8083 0.9792
5
+ 4 ref 0.9068 0.0581 0.8039 0.9780
6
+ 5 ref 0.9011 0.0588 0.7955 0.9749
7
+ 6 ref 0.8776 0.0636 0.7567 0.9670
8
+ 7 best 0.8697 0.0526 0.7404 0.9661
9
+ 8 dstb 0.8563 0.0523 0.7233 0.9562
10
+ 9 dst 0.8561 0.0459 0.7196 0.9575
11
+ 10 ref 0.8555 0.0430 0.7221 0.9592
12
+ 11 ref 0.8534 0.0619 0.7168 0.9560
13
+ 12 dstb 0.8513 0.0463 0.7131 0.9557
14
+ 13 b16 0.8466 0.0473 0.7104 0.9523
15
+ 14 dst 0.8455 0.0522 0.7120 0.9484
16
+ 15 s16 0.8450 0.0571 0.7113 0.9499
17
+ 16 ref 0.8403 0.0630 0.6999 0.9510
18
+ 17 b16 0.8400 0.0600 0.7060 0.9464
19
+ 18 dstb 0.8395 0.0488 0.7010 0.9466
20
+ 19 dst 0.8384 0.0661 0.6950 0.9467
21
+ 20 s16 0.8313 0.0576 0.6912 0.9424
22
+ 21 s16 0.8311 0.0708 0.6934 0.9406
23
+ 22 s16 0.8297 0.0698 0.6858 0.9414
24
+ 23 dst 0.8282 0.0768 0.6896 0.9381
25
+ 24 s16 0.8271 0.0469 0.6819 0.9411
26
+ 25 s16 0.8268 0.0484 0.6847 0.9397
27
+ 26 b16 0.8200 0.0468 0.6712 0.9402
28
+ 27 s16 0.8166 0.0577 0.6669 0.9323
29
+ 28 b16 0.8134 0.0514 0.6647 0.9337
30
+ 29 dst 0.8092 0.0595 0.6584 0.9315
31
+ 30 dst 0.8079 0.0443 0.6530 0.9309
32
+ 31 dst 0.8068 0.0569 0.6568 0.9323
33
+ 32 s16 0.8018 0.0452 0.6458 0.9284
34
+ 33 s16 0.7987 0.0733 0.6483 0.9223
35
+ 34 ctl 0.7939 0.0569 0.6338 0.9258
36
+ 35 s16 0.7855 0.0834 0.6283 0.9173
37
+ 36 b16 0.7561 0.0539 0.5906 0.8958
38
+ 37 ctl 0.7303 0.0726 0.5603 0.8800
39
+ 38 ctl 0.6613 0.0651 0.4784 0.8224
data/paper/book-data/trackA_dot_her2-yale_rows.dat ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ y label
2
+ 1 H-optimus-0, card norm., CLS, 1.0\,\textmu m/px
3
+ 2 H-optimus-0, card norm., CLS
4
+ 3 H-optimus-0, card norm., CLS+mean
5
+ 4 H-optimus-0, ImageNet norm. (Aug.)
6
+ 5 Phikon v1, ViT-B/16 (Aug.)
7
+ 6 Midnight-12k, CLS+mean
8
+ 7 \textbf{\textcolor{hrBest}{D16: H-optimus-0, 5k, from final}}
9
+ 8 \textbf{\textcolor{hrB16!80!black}{D18: H-optimus-0, ViT-B/16, 5k, from step 40k}}
10
+ 9 D14: H-optimus-0 teacher, 20k steps
11
+ 10 Midnight-12k, CLS
12
+ 11 Hibou-B (Aug.)
13
+ 12 D18: H-optimus-0, ViT-B/16, 5k, from step 50k
14
+ 13 ssl-vitb16 step 35k
15
+ 14 D16: H-optimus-0, 5k, from step 50k
16
+ 15 ssl-vits16 step 55k
17
+ 16 Midnight-12k, CLS, 1.0\,\textmu m/px
18
+ 17 ssl-vitb16 step 40k
19
+ 18 D18: H-optimus-0, ViT-B/16, 5k, from step 45k
20
+ 19 D13: Midnight-12k teacher, 20k steps
21
+ 20 ssl-vits16 step 35k
22
+ 21 ssl-vits16 step 50k
23
+ 22 ssl-vits16 step 40k
24
+ 23 D16: H-optimus-0, 5k, from random
25
+ 24 ssl-vits16 step 60k
26
+ 25 ssl-vits16 final (93k)
27
+ 26 ssl-vitb16 step 45k
28
+ 27 ssl-vits16 step 45k
29
+ 28 ssl-vitb16 step 20k
30
+ 29 D15: Midnight, 5k, from final
31
+ 30 D15: Midnight, 5k, from step 50k
32
+ 31 D15: Midnight, 5k, from random
33
+ 32 ssl-vits16 step 65k
34
+ 33 ssl-vits16 step 20k
35
+ 34 DINOv2 ViT-S/14 (natural images)
36
+ 35 ssl-vits16 step 5k
37
+ 36 ssl-vitb16 step 10k
38
+ 37 ResNet-50, ImageNet (Aug.)
39
+ 38 random weights, ViT-S/16
data/paper/paper-data/fig_ladder.tex ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ % Generated by docs/paper/paper_data.py
2
+ \nextgroupplot[title={\YY}]
3
+ \addplot[blue!70!black, mark=*, mark size=1.8pt] coordinates {(0,0.7610) (1,0.8580) (2,0.8497) (3,0.8440)};
4
+ \addplot[red!70!black, dashed, domain=-0.3:3.3, samples=2] {0.8720};
5
+ \addplot[black!50, dotted, domain=-0.3:3.3, samples=2] {0.8970};
6
+ \nextgroupplot[title={\TT}]
7
+ \addplot[blue!70!black, mark=*, mark size=1.8pt] coordinates {(0,0.5890) (1,0.7050) (2,0.6877) (3,0.6900)};
8
+ \addplot[red!70!black, dashed, domain=-0.3:3.3, samples=2] {0.6790};
9
+ \addplot[black!50, dotted, domain=-0.3:3.3, samples=2] {0.6760};
10
+ \nextgroupplot[title={\TY}]
11
+ \addplot[blue!70!black, mark=*, mark size=1.8pt] coordinates {(0,0.5890) (1,0.7620) (2,0.7950) (3,0.8120)};
12
+ \addplot[red!70!black, dashed, domain=-0.3:3.3, samples=2] {0.8110};
13
+ \addplot[black!50, dotted, domain=-0.3:3.3, samples=2] {0.8050};
14
+ \nextgroupplot[title={\YT}]
15
+ \addplot[blue!70!black, mark=*, mark size=1.8pt] coordinates {(0,0.5200) (1,0.6250) (2,0.6423) (3,0.6500)};
16
+ \addplot[red!70!black, dashed, domain=-0.3:3.3, samples=2] {0.6620};
17
+ \addplot[black!50, dotted, domain=-0.3:3.3, samples=2] {0.6530};
data/paper/paper-data/her2tasks/fish/dinov2s/s1.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
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5
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7
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data/paper/paper-data/her2tasks/fish/dinov2s/s10.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
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2
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3
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4
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5
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6
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7
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data/paper/paper-data/her2tasks/fish/dinov2s/s2.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
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3
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4
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5
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6
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7
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data/paper/paper-data/her2tasks/fish/dinov2s/s3.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
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3
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4
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5
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6
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7
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data/paper/paper-data/her2tasks/fish/dinov2s/s4.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
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3
+ fold,1,21,0,0.588889,29,9,20,0.622222,0.115417,0.396008,0.848436,0.411111,0.861174,0.614520,0.777778,0.250000,0.318182,0.714286,0.513889,0.413793,0.451613
4
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5
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6
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7
+ pooled,-1,0,0,0.476228,143,44,99,0.451102,0.052074,0.349038,0.553166,0.348614,0.547901,0.500000,0.318182,0.646465,0.285714,0.680851,0.482323,0.545455,0.301075
data/paper/paper-data/her2tasks/fish/dinov2s/s5.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
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2
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3
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4
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5
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6
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7
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data/paper/paper-data/her2tasks/fish/dinov2s/s6.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ scope,fold,epochs_run,best_epoch,val_auc,n,n_pos,n_neg,auc,auc_se,auc_lo,auc_hi,boot_lo,boot_hi,threshold,sensitivity,specificity,ppv,npv,balanced_accuracy,accuracy,f1
2
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3
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4
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5
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6
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7
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data/paper/paper-data/her2tasks/fish/dinov2s/s7.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
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2
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3
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4
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5
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6
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7
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data/paper/paper-data/her2tasks/fish/dinov2s/s8.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ scope,fold,epochs_run,best_epoch,val_auc,n,n_pos,n_neg,auc,auc_se,auc_lo,auc_hi,boot_lo,boot_hi,threshold,sensitivity,specificity,ppv,npv,balanced_accuracy,accuracy,f1
2
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3
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4
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5
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6
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7
+ pooled,-1,0,0,0.442632,143,44,99,0.440312,0.051928,0.338535,0.542090,0.345133,0.535431,0.500000,0.136364,0.838384,0.272727,0.685950,0.487374,0.622378,0.181818
data/paper/paper-data/her2tasks/fish/dinov2s/s9.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ scope,fold,epochs_run,best_epoch,val_auc,n,n_pos,n_neg,auc,auc_se,auc_lo,auc_hi,boot_lo,boot_hi,threshold,sensitivity,specificity,ppv,npv,balanced_accuracy,accuracy,f1
2
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3
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4
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5
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6
+ fold,4,23,2,0.577778,27,8,19,0.486842,0.118525,0.254537,0.719148,0.245901,0.722222,0.241184,0.500000,0.526316,0.307692,0.714286,0.513158,0.518519,0.380952
7
+ pooled,-1,0,0,0.500702,143,44,99,0.504132,0.054297,0.397711,0.610553,0.402113,0.608662,0.500000,0.340909,0.696970,0.333333,0.704082,0.518939,0.587413,0.337079
data/paper/paper-data/her2tasks/fish/hibou/s1.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ scope,fold,epochs_run,best_epoch,val_auc,n,n_pos,n_neg,auc,auc_se,auc_lo,auc_hi,boot_lo,boot_hi,threshold,sensitivity,specificity,ppv,npv,balanced_accuracy,accuracy,f1
2
+ fold,0,26,5,0.505556,29,9,20,0.350000,0.139123,0.077325,0.622675,0.103835,0.642909,0.614754,0.222222,0.800000,0.333333,0.695652,0.511111,0.620690,0.266667
3
+ fold,1,23,2,0.577778,29,9,20,0.444444,0.106966,0.234795,0.654094,0.240258,0.655563,0.123769,0.666667,0.350000,0.315789,0.700000,0.508333,0.448276,0.428571
4
+ fold,2,26,5,0.500000,29,9,20,0.616667,0.106839,0.407267,0.826066,0.416645,0.811594,0.123355,0.333333,0.700000,0.333333,0.700000,0.516667,0.586207,0.333333
5
+ fold,3,29,8,0.611842,29,9,20,0.461111,0.130570,0.205199,0.717023,0.216645,0.722283,0.442227,0.222222,0.700000,0.250000,0.666667,0.461111,0.551724,0.235294
6
+ fold,4,37,16,0.788889,27,8,19,0.486842,0.125871,0.240140,0.733544,0.238623,0.742857,0.093539,0.375000,0.578947,0.272727,0.687500,0.476974,0.518519,0.315789
7
+ pooled,-1,0,0,0.471813,143,44,99,0.460973,0.051849,0.359352,0.562595,0.365382,0.559180,0.500000,0.159091,0.848485,0.318182,0.694215,0.503788,0.636364,0.212121
data/paper/paper-data/her2tasks/fish/hibou/s10.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ scope,fold,epochs_run,best_epoch,val_auc,n,n_pos,n_neg,auc,auc_se,auc_lo,auc_hi,boot_lo,boot_hi,threshold,sensitivity,specificity,ppv,npv,balanced_accuracy,accuracy,f1
2
+ fold,0,28,7,0.438889,29,9,20,0.311111,0.126971,0.062252,0.559970,0.077768,0.577922,0.394765,0.222222,0.900000,0.500000,0.720000,0.561111,0.689655,0.307692
3
+ fold,1,23,2,0.627778,29,9,20,0.483333,0.110249,0.267250,0.699417,0.267564,0.685743,0.299380,0.888889,0.400000,0.400000,0.888889,0.644444,0.551724,0.551724
4
+ fold,2,34,13,0.516667,29,9,20,0.511111,0.116236,0.283293,0.738929,0.285677,0.745155,0.749418,0.111111,0.800000,0.200000,0.666667,0.455556,0.586207,0.142857
5
+ fold,3,38,17,0.578947,29,9,20,0.505556,0.123167,0.264152,0.746959,0.249803,0.744058,0.832705,0.333333,0.750000,0.375000,0.714286,0.541667,0.620690,0.352941
6
+ fold,4,33,12,0.822222,27,8,19,0.368421,0.115243,0.142550,0.594293,0.144690,0.611842,0.020081,0.625000,0.263158,0.263158,0.625000,0.444079,0.370370,0.370370
7
+ pooled,-1,0,0,0.435906,143,44,99,0.453627,0.053372,0.349020,0.558234,0.356260,0.554070,0.500000,0.204545,0.777778,0.290323,0.687500,0.491162,0.601399,0.240000
data/paper/paper-data/her2tasks/fish/hibou/s2.csv ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ scope,fold,epochs_run,best_epoch,val_auc,n,n_pos,n_neg,auc,auc_se,auc_lo,auc_hi,boot_lo,boot_hi,threshold,sensitivity,specificity,ppv,npv,balanced_accuracy,accuracy,f1
2
+ fold,0,21,0,0.622222,29,9,20,0.438889,0.122888,0.198032,0.679745,0.208185,0.682708,0.405420,0.333333,0.650000,0.300000,0.684211,0.491667,0.551724,0.315789
3
+ fold,1,22,1,0.572222,29,9,20,0.438889,0.109287,0.224690,0.653087,0.209494,0.678607,0.283015,0.666667,0.300000,0.300000,0.666667,0.483333,0.413793,0.413793
4
+ fold,2,23,2,0.544444,29,9,20,0.600000,0.117680,0.369351,0.830649,0.374716,0.816667,0.220665,0.333333,0.600000,0.272727,0.666667,0.466667,0.517241,0.300000
5
+ fold,3,27,6,0.618421,29,9,20,0.522222,0.126458,0.274368,0.770076,0.282524,0.757895,0.293569,0.444444,0.500000,0.285714,0.666667,0.472222,0.482759,0.347826
6
+ fold,4,40,19,0.838889,27,8,19,0.506579,0.129399,0.252961,0.760197,0.269522,0.746921,0.073867,0.625000,0.421053,0.312500,0.727273,0.523026,0.481481,0.416667
7
+ pooled,-1,0,0,0.501316,143,44,99,0.491965,0.052029,0.389990,0.593940,0.396156,0.596247,0.500000,0.204545,0.777778,0.290323,0.687500,0.491162,0.601399,0.240000