Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261013T023822Z-pbisc-yellow-scsemi-blue/diffusion/dataset/server_1/model8/presentations/2026-09-30--paper-summary--r00/data/method_palette_20261013/yellow_revision/before_REPORT.md

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+# PBISC red and scSemiProfiler blue throughout the current deck
+
+User directive: use red-family colors for PBISC and blue-family colors for scSemiProfiler across the entire deck.
+
+## Applied design
+
+The current 34-slide results review uses PBISC #B2182B and scSemiProfiler #2166AC. PBISC raw/calibrated inputs, full fine-tuning, sc-only fine-tuning, gene panels, cross-cohort variants and scratch ablation use distinguishable red/rose shades. scSemi training/inference and modified readout use blue shades; hatch patterns are retained. CIBERSORTx is purple and BayesPrism remains green.
+
+25 scientific figure assets were recolored. Seven assets whose color encodes input data, cell type, cohort or observed abundance remain unchanged. The Figure 1 model blocks/arrows and adaptation box are red-family; expression values, detection, bulk and biological categories retain their independent semantic encodings. The conditioning-only diagram keeps its context color.
+
+The policy is explicit per figure (`palette.json`), because the same old RGB denoted different entities in different panels. The current deck builder always applies it. Original 76-slide artifacts remain intact; review variants live in `figures/method_palette_20261013/`.
+
+## Preservation and validation
+
+Native PDF paint colors were edited; plot coordinates, text, numbers, uncertainty geometry, cell images and plotting data were not changed. Marker Form objects and colored hatch patterns were included. Four black pseudobulk-input reconstruction rectangles were scoped individually to avoid recoloring black text or axes. Per-figure receipts verify the serialized files.
+
+Verified: 34-slide PPTX/PDF; 25 recolored assets; seven non-method assets preserved; 86 numerical CSV hashes unchanged; all derived summary numbers and slide text unchanged; all 180 source hashes verified; no old mapped method colors remain. Original source geometry/text and embedded raster payloads pass preservation checks. Whole-deck contact sheets and method-comparison slides were visually inspected.
+
+No training, generation or scoring was started. Only presentation assets were revised. Private versioned archive maintenance records the exact current files, with prior versions preserved.

paper-releases/pbisc-diffusion/updates/20261013T023822Z-pbisc-yellow-scsemi-blue/diffusion/dataset/server_1/model8/presentations/2026-09-30--paper-summary--r00/data/method_palette_20261013/yellow_revision/before_build_results_review_20261013.py

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+"""Build the reviewed 34-slide deck with the original 76-slide renderer/style.
+
+CPU only. Existing figures are reused intact; new plots read small saved CSVs.
+The original deck and its specification are never rewritten.
+"""
+from pathlib import Path
+from datetime import datetime, timezone, timedelta
+import copy
+import csv
+import hashlib
+import json
+import os
+import sys
+import tempfile
+
+if os.environ.get('CUDA_VISIBLE_DEVICES') != '':
+    raise SystemExit('Set CUDA_VISIBLE_DEVICES empty for this CPU-only builder')
+D = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(D))
+import generate_deck as original
+from pptx import Presentation
+from pptx.util import Inches
+from results_review_style_plots import build as build_plots
+from results_review_style_panels import build as build_panels
+from review_palette_pdf import recolor_pdf, render_pdf_to_png
+
+DATA = D/'data'
+ORIGINAL = json.loads((DATA/'slides_spec.json').read_text())['slides']
+PREVIOUS = json.loads((DATA/'style_review_20261013/before_results_review_20261013_provenance.json').read_text())
+STEM = D/'PBISC-Diffusion_results_review_20261013'
+SOURCES = {}
+
+
+def apply_method_palette(slides):
+    """Use figure-specific method roles; preserve biology and numerical geometry."""
+    policy_path=source(DATA/'method_palette_20261013/palette.json','user-approved method colour policy')
+    policy=json.loads(policy_path.read_text())
+    target=D/'figures/method_palette_20261013'
+    target.mkdir(exist_ok=True)
+    records=[]
+    converted={}
+    for slide_spec in slides:
+        originals=list(slide_spec.get('figures',[]))
+        if originals: slide_spec['figures_before_palette']=originals
+        replacements=[]
+        for original_asset in originals:
+            asset_path=D/original_asset
+            stem=asset_path.stem
+            rule=policy['rules'][stem]  # unknown assets require an explicit semantic policy
+            if not rule['mapping'] and not rule.get('rectangle_rules'):
+                replacements.append(original_asset)
+                records.append({'asset':original_asset,'action':'preserved','reason':rule['reason']})
+                continue
+            if stem not in converted:
+                input_pdf=source(rule.get('source_pdf',asset_path.with_suffix('.pdf')),'original vector figure for method recolouring')
+                input_png=source(asset_path,'original figure image')
+                output_pdf=target/(stem+'.pdf'); output_png=target/(stem+'.png')
+                with tempfile.TemporaryDirectory(prefix='.build-',dir=target) as tmp:
+                    candidate_pdf=Path(tmp)/(stem+'.pdf');candidate_png=Path(tmp)/(stem+'.png')
+                    proof=recolor_pdf(input_pdf,candidate_pdf,rule['mapping'],
+                        rectangle_rules=rule.get('rectangle_rules'),
+                        rgb_tolerance=5.1e-7 if stem=='fig1b_overview_nature' else 1e-8)
+                    render=render_pdf_to_png(candidate_pdf,candidate_png,dpi=300 if stem=='fig1b_overview_nature' else 200)
+                    candidate_pdf.replace(output_pdf);candidate_png.replace(output_png)
+                proof['destination']=str(output_pdf)
+                render['pdf']=str(output_pdf);render['png']=str(output_png)
+                proof.update({'render':render,'original_png':str(input_png),'original_png_sha256':sha(input_png),
+                              'semantic_reason':rule['reason'],'policy_sha256':sha(policy_path)})
+                proof_path=target/(stem+'.palette.json')
+                proof_path.write_text(json.dumps(proof,indent=2)+'\n')
+                for path in (output_pdf,output_png,proof_path):source(path,'method palette variant or preservation proof')
+                converted[stem]=relative(output_png)
+                records.append({'asset':original_asset,'action':'recolored','output':relative(output_png),
+                    'proof':relative(proof_path),'reason':rule['reason'],
+                    'preservation_pass':proof['preservation_pass']})
+            replacements.append(converted[stem])
+        if originals:slide_spec['figures']=replacements
+    catalog={'schema':'pbisc.deck-method-palette.v1','primary':policy['primary'],
+             'recolored_figures':len(converted),'records':records}
+    catalog_path=DATA/'method_palette_20261013/ASSET_MAP.json'
+    catalog_path.write_text(json.dumps(catalog,indent=2)+'\n')
+    source(catalog_path,'method palette coverage and per-figure proof locations')
+    return catalog
+
+
+def sha(path):
+    with Path(path).open('rb') as f:
+        return hashlib.file_digest(f,'sha256').hexdigest()
+
+
+def source(path, role):
+    path=Path(path).resolve()
+    if not path.is_file():
+        raise FileNotFoundError(path)
+    SOURCES[str(path)]={'sha256':sha(path),'role':role}
+    return path
+
+
+def relative(path):
+    return str(Path(path).resolve().relative_to(D))
+
+
+def from_original(number, title, section, protocol, keywords=None):
+    item=copy.deepcopy(ORIGINAL[number-1])
+    assert item['kind']=='content'
+    item.update(title=title,section_label=section,footnote=protocol,original_slide=number)
+    item['footnote_full']=protocol+'\nOriginal context: '+item.get('footnote_full',item.get('footnote',''))
+    if keywords is not None:
+        item['keywords']=keywords
+    # The original reference line remains visible when it fits. Full citations
+    # always stay in notes, unchanged from the original source specification.
+    if item.get('refs') and len(original.wrap(protocol,original.FOOT_PT,original.FOOT_W))>1:
+        item.pop('refs')
+    return item
+
+
+def fresh(title,section,protocol,asset,keywords=()):
+    return {'kind':'content','title':title,'section_label':section,'layout':'full',
+            'figures':[relative(Path(asset).with_suffix('.png'))],
+            'keywords':list(keywords),'footnote':protocol,'footnote_full':protocol,
+            'sources':str(asset)}
+
+
+def main():
+    plots=build_plots()
+    panels=build_panels()
+    for row in plots['inputs']:
+        source(row['path'],row.get('role','saved plot data'))
+    for path in plots['assets']:
+        source(path,'restyled saved-table plot')
+    for value in panels.values():
+        for key in ('png','pdf','svg','provenance'):
+            if value.get(key):
+                source(value[key],'restyled panel '+key)
+        proof=json.loads(Path(value['provenance']).read_text())
+        # Preserve the complete panel-specific evidence even if its schema differs.
+        for field in ('inputs','sources'):
+            rows=proof.get(field,[])
+            if isinstance(rows,dict): rows=[{'path':p} for p in rows]
+            for row in rows:
+                p=row.get('path',row.get('source')) if isinstance(row,dict) else row
+                if p: source(p,'saved panel data')
+    comp,rareobs,rarecompare=plots['figures']
+    slides=[
+        {'kind':'title','title':'PBISC-Diffusion','subtitle':'Results review · existing evidence and protocol updates · 13 October 2026'},
+        {'kind':'agenda','title':'Six figures: evidence available now','items':[
+            'Fig. 1  Pretraining, diffusion and bulk conditioning',
+            'Fig. 2  Model design and paired-data requirements',
+            'Fig. 3  Healthy reconstruction: quality, composition and time',
+            'Fig. 4  Disease signals and deconvolution benchmarks',
+            'Fig. 5  Rare cell states: corrected analysis of existing outputs',
+            'Fig. 6  Bulk-only reproduction: awaiting the new dataset']},
+    ]
+    slides += [
+        from_original(7,'PBISC-Diffusion: pretraining to generated cells','Fig. 1a',
+            'Schematic. Conditioning recipe size and the number of generated cells are distinct; no cell-type quotas.',
+            []),
+        from_original(8,'Bulk conditioning','Fig. 1b',
+            'Final 6k model. Recipe size K conditions the bulk; the number of generated cells is chosen separately.',
+            ['One shared bulk condition; independent cell draws', 'Expression, depth and measured-gene masks', 'No cell-type or disease labels as model input']),
+        from_original(9,'Pretraining corpus','Fig. 1c',
+            'Corpus labels describe the data; they are not model inputs. Dataset composition is not sampler exposure.'),
+        fresh('Native-pseudobulk model comparisons','Fig. 2a',
+            'Completed held-out rescoring. Architecture: 1% detection floor; gene-panel comparison: 0.1% floor.',panels['ablation']['pdf']),
+        from_original(12,'Gene panels: performance and coverage','Fig. 2b',
+            'Existing panel benchmark. 6k: five sampling seeds; other panels: one seed. Different axis from the architecture sweep.'),
+        fresh('Healthy bulk: full fine-tuning and LoRA rank','Fig. 2c',
+            'Original donor-level five-fold comparison. LoRA rank 16 is a quality/parameter compromise.',panels['rank']['pdf']),
+    ]
+    # Preserve the audited scope of every retained result. Figure assets and
+    # takeaways are reused from the original 76-slide deck, without cropping.
+    mapping=[
+        (31,'Historical paired-data learning curve','Fig. 2d'),
+        (26,'Additional pairs improve donor-level information','Fig. 2e'),
+        (17,'Measured bulk differs from pseudobulk','Fig. 3a'),
+        (30,'Healthy donors: exactly five paired samples','Fig. 3b'),
+    ]
+    for position,(old,title,label) in enumerate(mapping,start=8):
+        assert PREVIOUS['slides'][position]['old_deck_slide']==old
+        p=PREVIOUS['slides'][position]['protocol']
+        if old==31:
+            p='LoRA: n training + 7 validation. scSemi: n + 7 representatives, with CV-HVG reuse. Not the strict total-n protocol.'
+        slides.append(from_original(old,title,label,p))
+    slides.append(fresh('Composition: error and donor-level wins','Fig. 3c',
+        'Exactly five pairs per draw. Absolute errors averaged within each held-out donor; 107 donors, equal weight. Descriptive.',comp))
+    mapping=[
+        (32,'Representative-dependent composition','Fig. 3d'),
+        (34,'Adaptation and generation time','Fig. 3e'),
+        (37,'Paired cohorts and evaluation units','Fig. 4a'),
+        (38,'Disease signals: five-donor draws','Fig. 4b'),
+        (39,'Disease signals: five-fold validation','Fig. 4c'),
+        (40,'Disease-gene agreement across list lengths','Fig. 4d'),
+        (41,'Cell-type expression: deconvolution comparison','Fig. 4e'),
+        (46,'Composition: deconvolution comparison','Fig. 4f'),
+    ]
+    for position,(old,title,label) in enumerate(mapping,start=13):
+        assert PREVIOUS['slides'][position]['old_deck_slide']==old
+        p=PREVIOUS['slides'][position]['protocol']
+        kws=None
+        if old==32:
+            kws=['Composition varies with the selected representative',
+                 'Compare generated fractions with held-out observed fractions']
+        elif old==37:
+            kws=['403 paired samples, 275 donors',
+                 'Identity screening where available; donor-level splits',
+                 'Ji bulk: whole blood, not PBMC']
+        elif old==46:
+            kws=['PBISC closer than BayesPrism in 22/25 draws, than CIBERSORTx in 24/25',
+                 'Composition compared with held-out observed cells',
+                 'Five-fold: PBISC lowest error in 4 of 5 cohorts']
+        slides.append(from_original(old,title,label,p,kws))
+    slides += [
+        fresh('Rare-state frequencies in observed cells','Fig. 5a',
+            'Original five-donor outputs. Median across draws; state share within its parent population. Controls included.',rareobs),
+        fresh('Rare-state fidelity: zero-aware reanalysis','Fig. 5b',
+            'Original five-donor outputs; zero draws retained and actual donor IDs. 59 state/cohort combinations, including controls.',rarecompare),
+        fresh('Behcet: one-gene and multi-gene C1Q rules','Fig. 5c',
+            'Descriptive: unmatched reference includes training donors. Same three pairs; two identity-pass and one uncertain.',panels['behcet']['pdf']),
+        {'kind':'status','title':'Remaining work','section_label':'Figure status',
+         'rows':[
+            ['Protocol updates','Total n = 5/10/20/40 without extra validation; exact-five samples in multi-visit cohorts.'],
+            ['Analysis of existing outputs','Patient-aware contrasts, rare-state scoring and healthy cell visualizations.'],
+            ['Figure 6: new data','Reproduce a published finding in the user-prepared bulk-only cohort.']],
+         'footnote':'Existing results remain visible. Protocol updates and missing-data work are identified separately.'},
+    ]
+    mapping=[
+        (19,'Control-cell embedding diagnostic'),
+        (58,'Generated-cell quality across cohorts'),
+        (60,'Precision and coverage across neighbourhood sizes'),
+        (62,'Same training pairs: five-fold comparison'),
+        (68,'Cross-cohort pairs do not replace local pairs'),
+        (69,'Longer cross-cohort training leaves a gap'),
+        (70,'From-scratch control: evidence and limits'),
+        (74,'scSemiProfiler readout sensitivity'),
+        (42,'SLE pseudobulk development benchmark'),
+    ]
+    for position,(old,title) in enumerate(mapping,start=25):
+        assert PREVIOUS['slides'][position]['old_deck_slide']==old
+        p=PREVIOUS['slides'][position]['protocol']
+        slides.append(from_original(old,title,'Supporting',p))
+    assert len(slides)==34
+    palette=apply_method_palette(slides)
+    prs=Presentation();prs.slide_width=Inches(original.SLIDE_W);prs.slide_height=Inches(original.SLIDE_H)
+    for i,s in enumerate(slides,start=1):
+        kind=s['kind']
+        if kind=='title': original.build_title(prs,s)
+        elif kind=='agenda': original.build_agenda(prs,s,i)
+        elif kind=='status':
+            slide=prs.slides.add_slide(prs.slide_layouts[6]);original.white_bg(slide)
+            original.add_title(slide,s['title'],s['section_label'])
+            for row,(title,body) in enumerate(s['rows']):
+                y=1.35+row*1.55
+                original.add_text(slide,original.X0,y,11.6,.4,[title],20,bold=True)
+                original.add_text(slide,original.X0,y+.5,11.6,.8,[body],16,color=original.GREY)
+            original.add_footer(slide,s['footnote'],i)
+        else:
+            original.build_content(prs,s,i)
+        for f in s.get('figures',[]):
+            source(D/f,'figure reused intact' if s.get('original_slide') else 'restyled figure')
+            vector=(D/f).with_suffix('.pdf')
+            if vector.is_file(): source(vector,'figure vector companion')
+        for sh in prs.slides[-1].shapes:
+            assert sh.left>=0 and sh.top>=0 and sh.left+sh.width<=prs.slide_width+2 and sh.top+sh.height<=prs.slide_height+2,(i,sh.name)
+    prs.save(STEM.with_suffix('.pptx'))
+    for p in [D/'generate_deck.py',D/'tools/style.py',DATA/'slides_spec.json',
+              Path(__file__),D/'tools/results_review_style_plots.py',D/'tools/results_review_style_panels.py',
+              DATA/'style_review_20261013/before_results_review_20261013_provenance.json',
+              D/'tools/review_palette_pdf.py']:
+        source(p,'renderer, style or audited content source')
+    spec={'deck':{'output_pptx':STEM.name+'.pptx','style_source':'generate_deck.py + tools/style.py'},'slides':slides}
+    (DATA/'results_review_20261013_spec.json').write_text(json.dumps(spec,indent=2)+'\n')
+    manifest={'schema':'pbisc.results-review.reuse.v2','style_revision':4,
+        'as_of_kst':datetime.now(timezone(timedelta(hours=9))).isoformat(),
+        'slides':slides,'sources':SOURCES,'new_training':False,'new_generation':False,
+        'cpu_work':'Saved CSV plots; healthy composition now compares paired absolute errors and donor wins. No new model outputs.',
+        'plot_calculations':plots.get('calculations'), 'panel_outputs':panels,
+        'method_palette':palette,
+        'pptx_sha256':sha(STEM.with_suffix('.pptx')),'pdf_status':'awaiting PPTX export and visual verification'}
+    (DATA/'results_review_20261013_provenance.json').write_text(json.dumps(manifest,indent=2)+'\n')
+    with (DATA/'results_review_20261013_slide_map.csv').open('w') as f:
+        w=csv.DictWriter(f,fieldnames=['slide','section','title','protocol','old_deck_slide']);w.writeheader()
+        for i,s in enumerate(slides,1):w.writerow({'slide':i,'section':s.get('section_label',''),
+            'title':s['title'],'protocol':s.get('footnote',''),'old_deck_slide':s.get('original_slide','')})
+    print(json.dumps({'slides':len(slides),'sources':len(SOURCES),'pptx':str(STEM.with_suffix('.pptx'))}))
+
+
+if __name__=='__main__':main()

paper-releases/pbisc-diffusion/updates/20261013T023822Z-pbisc-yellow-scsemi-blue/diffusion/metadata/inference_locations.json

@@ -0,0 +1,5 @@
+{
+  "locations": [],
+  "project_id": "pbisc-diffusion",
+  "update_id": "20261013T023822Z-pbisc-yellow-scsemi-blue"
+}

paper-releases/pbisc-diffusion/updates/20261013T023822Z-pbisc-yellow-scsemi-blue/diffusion/metadata/request.json

@@ -0,0 +1,841 @@
+{
+  "assets": [
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/README.md",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/PBISC-Diffusion_results_review_20261013.pdf",
+      "state": "intermediate"
+    },
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/PBISC-Diffusion_results_review_20261013.pptx",
+      "state": "intermediate"
+    },
+    {
+      "host": "server_1",
+      "kind": "code",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/tools/build_results_review_20261013.py",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "code",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/tools/results_review_style_plots.py",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "code",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/tools/results_review_style_panels.py",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/data/results_review_20261013_provenance.json",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/data/results_review_20261013_slide_map.csv",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/data/results_review_20261013_spec.json",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "figure",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/review_style_20261013_healthy_composition.png",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/review_style_20261013_healthy_composition.pdf",
+      "state": "intermediate"
+    },
+    {
+      "host": "server_1",
+      "kind": "figure",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/review_style_20261013_healthy_composition.svg",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "figure",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/review_style_20261013_rare_observed.png",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "report",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/review_style_20261013_rare_observed.pdf",
+      "state": "intermediate"
+    },
+    {
+      "host": "server_1",
+      "kind": "figure",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/review_style_20261013_rare_observed.svg",
+      "state": "completed"
+    },
+    {
+      "host": "server_1",
+      "kind": "figure",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/review_style_20261013_rare_corrected_comparison.png",
+      "state": "completed"
+    },
+    {
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