AtlasOpenCoder / MANIFEST_PAPER1.md
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AtlasOpenCoder v1: the battery, the artefacts and both papers' manifests
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Paper 1 — where every number comes from

One row per number, grouped by paragraph, in paragraph order. A row gives the number as the paper prints it, the artefact file it is read from, the field inside that file, and the script that rebuilds the artefact. Paths are relative to the dataset's root. Each script is in experiments/ of one of the two code repositories — AtlasCalibratedConceptProfiles for the method, its checks and the inventory, AtlasRepresentationalDrift for the drift analysis. Which one does not follow from the file's directory: validation/paper1/ and validation/paper2/ record which paper's script wrote a file, and several files under validation/paper2/ were written by scripts in the first repository.

Every number printed in the paper is listed, including the ones that cannot be checked against a released file: those are marked FLAGGED or unstored and are collected in their own section below, with what the record does hold in their place.

How a number is traced

mark what it means
key the field's key names the quantity the sentence names, and its value agrees
count a small integer traced to the field that defines it (n_*, *_count, or a key), not matched by value
value a distinctive number (≥ 2 decimal places, or an integer ≥ 1,000) matched by value, in an artefact whose field shares a word with the sentence
canon a recurring quantity — a token count, or a defining count such as 169 or 7,373 — sent to the one field that defines it by a rule, never matched by value
unstored the number is right and its artefact is named, but the summary field it quotes is not stored — a count or median the script computes and discards
sibling the value sits in the same stored entry as a field already traced in that paragraph — an interval bound beside its point, a first beside its last
declared a declared setting or rule parameter, stored as a key or a definition field
derived arithmetic on stored fields; the arithmetic is given in the row
cited a number from cited work, not ours
FLAGGED resolved by hand and does not reproduce as written; see the section on numbers that do not reproduce

Two classes of numeral are excluded before counting, because they are not quantities: model names (OpenCoder-1.5B, Pythia-1.4B), cross-references (§3.1–3.3, D.1, [TBC: A1.3]), and list enumerators ((3) at least two checkpoints, statements 2 and 3, item 4).

Counts, per number

distinctive count one-place total
key 128 38 27 193
count 113 113
canon 20 28 48
value 36 36
sibling 28 5 33
declared 2 7 3 12
derived 2 10 7 19
cited 1 1
unstored 1 1
FLAGGED 2 2
total 217 202 39 458

1 number has no artefact at all — it is flagged below. Every other number resolves to a file and a field.

No row is left weak. Every number is tied to a field whose key names the quantity the sentence names, to a declared rule parameter, to arithmetic on stored fields that the row gives, or to cited work. The 1 unstored rows are the exception worth reading: the number is right and its artefact is named, but the summary it quotes — a count or a median the script computes and discards — is not in the file, so a reader cannot check it without re-running.

Numbers that do not reproduce from a released artefact

Three of this paper's numbers cannot be checked against a file in this dataset. They are named here rather than left for a reader to find.

  • §4.2's "2.4x further". The resolution figures live in validation/paper2/B10_SPACING_ADJUSTED.json, whose stored medians give a dense-to-tail ratio of 1.18 (median_per_1000_steps_dense 0.00784 against median_per_1000_steps_tail 0.00666). The printed 2.4x is the ratio of two twin-unit figures in the same paragraph -- 8.56 at the first 1,000-step pair over 3.56 at the end of period 1, both from that same artefact -- and no stored field holds the ratio itself.
  • Appendix D's pre-fix comparators, "against 1.2142" and "against 3.9%". Both come from the licence run that the fix of 19 October 2026 replaced, and that run's report is not part of the release; the appendix labels them as the superseded run's own. The two post-fix figures beside them are stored -- validation/paper1/RECHECK_PER_PROMPT.json gives median index 0.7455 and flagged share 0.0239 -- so the re-run's own numbers can be checked; the comparison against the run it replaced cannot.

Every other number in the paper resolves to a file and a field in this dataset.

The artefacts, and one line each confirming the field is the quantity

artefact numbers rebuild script the field is the quantity the paper names, because
validation/paper1/LICENCE_TABLE_CORRECTED.json 47 licence_table.py paper 1's checks after the four corrections; cited for the null's replicate count.
validation/paper2/ABLATION_NATS.json 32 ablation_nats.py the reliance claim: median_rise_over_random_nats is the carriers' loss rise minus the random sets' mean rise, in nats — the quantity §3.3 calls the cost of removal over a random set; old_set.* is the same for the set measured at 84 B. In nats, not control units, because the control's spread had not converged (ablation_nats.py measured that).
validation/paper2/ABLATION_RANKS.json 30 ablation_ranks.py the same removal experiment read as a rank: current.exact_one_sided_p and n_random are the one-sided position of the carriers among the random masks, which is what §3.3's 'cannot be separated from a random set' states.
validation/paper1/LENGTH_BAND_HELD.json 23 band_held.py paper 1's prompt-length check, cited in Appendix A item 10.
validation/paper1/CORE_COUNTS.json 21 core_counts.py the core families each construct's A set is built from — §3.1's counts of cores and prompts per construct.
validation/paper1/FOR_EXAMPLE.json 19 atlas.py for at the four references, the paper's worked example: norm_raw and norm_standardised are the concept profile's norm on the raw and standardised forms, which §4.8 artefact 2 contrasts; sparsity_* the same for sparsity.
validation/paper1/GATE_SHARES.json 15 - — not yet confirmed
validation/paper2/CEILINGS.json 15 ceilings.py the per-reference ceiling and carrier-set size at each cut (<cut>.median_size, chance).
validation/paper1/PROBE_MARGINS.json 13 probe_margins.py per_reference.<ref>.median_mean_margin is the median over constructs of a held-out prompt's signed distance from the probe's boundary, in the probe's own units — §4.7's one continuous reading — with median_control_mean_margin the same for the scrambled-label control.
validation/paper2/B16B_WEIGHT_NORMS.json 12 b16b_weight_norms.py per_checkpoint.<ref>.tensors.<matrix> are the Frobenius norms of layer 12's three MLP matrices — §4.3's 'the norms grow by 81%, 89% and 83%'.
validation/paper1/CHECK4_RELATIVE.json 10 check4_relative.py paper 1's check 4 recomputed on the suite's own metric; n_within_one_twin_unit = 4 is the figure §4.1 of paper 1 reports and paper 2 cites.
validation/paper1/LENGTHS.json 10 atlas.py prompt length per set and construct, behind check 3 and §3.2's length statements.
validation/paper1/RECHECK_PER_PROMPT.json 10 recheck_per_prompt.py the per-prompt re-check of the nulls; cited for its replicate count.
validation/paper2/B11_POWER.json 10 b11_power.py `dates.
validation/paper1/CHECK6_COMPANIONS.json 8 check6_companions.py n_companions per construct — the companion check Appendix A item 10 says is not met for the eight compound statements.
validation/paper1/LICENCE_TABLE.json 8 licence_table.py paper 1's nine checks per construct, cited in paper 2's Appendix A item 10.
validation/paper1/RECORD_SIZE.json 8 - new today. accumulators_gb_per_reference is the accumulator bytes over all 61 references divided by 61 — the 27.6 GB §2.4 and §3.3 quote; per_prompt_reference_gb the largest reference (107 GB); total_GB the 2,022 GB, which also appears as record_GATE_111.json :: dataset_bytes_gb.
calibration/checkpoints.json 7 checkpoint_inventory.py the checkpoint schedule (all[].step), which converts an iteration to a token count at 4,194,304 tokens per step.
record_GATE_111.json 7 - the recording gate: dataset_bytes_gb is the record's total size, and watched_ranges the three numbers that aborted a run when one fell out of band — twin agreement, concept norm and carrier overlap, the bands §3.4 quotes.
validation/paper1/CHECK6_REWEIGHT.json 7 check6_reweight.py the maximum-entropy re-weighting of the logged generator factors, with the LP feasibility proof and the effective sample size — check 6 as §4.8 and B.3 report it.
validation/paper1/POOLED_SETS_45.json 7 pooled_sets_169.py paper 1's family clustering, cited in paper 2 where it reports purity and cluster counts.
validation/paper1/SET_GRIDS.json 7 - — not yet confirmed
validation/r2/STEP3_SENSES_pretrain.json 7 - the three senses of 'settles' read on the standardised profile; `third_sense.*
validation/paper1/LOCATE_BY_CLASS.json 6 atlas.py where in the network a construct's response sits, by token class — §4.6.
validation/paper1/CHECK4_TWIN_UNITS.json 5 check4_twin_units.py check 4 in twin units, superseded for the paper by CHECK4_RELATIVE but kept because §B.1 quotes its conversion error: conversion_error_vs_stored_distance.{median,p95,max}_relative.
validation/paper1/FIGURES.json 5 atlas.py paper 1's figure data, cited where paper 2 quotes check 9.
validation/paper2/B18_RECURRENCE.json 5 b18_recurrence.py c_coordination_vs_circular_shift_median compares observed co-movement with a null that holds each neuron's own persistence — §4.2's 'what independent neurons with the same persistence would show'. The across-neuron shuffle in the same file (12.95) is a different null and is not that number.
validation/paper2/B1_ENTROPY.json 5 b1_entropy.py against_the_model.model_loss_governed_{early,last}_median_nats is the model's loss at governed positions at the first and last reference, and generator_marginal_entropy_governed_median_nats the loss of a reader who knows only the generator's rates — §5's three numbers.
validation/r2/STEP8_GRAPH_pretrain.json 5 - the unit-level graph: n_units = 147,456 is the product space, p8.n_fell_beyond_noise the departures beyond the noise unit, and partners[].factor the spacing factors.
validation/paper1/B_SUBTYPES.json 4 b_subtypes.py what each construct's B set is made of; cited in Appendix A item 1.
validation/paper1/FAMILIES.json 4 atlas.py per_cut.<k>.categories.<family>.<kind>.{purity,null_mean,largest_cluster_share} is how far a construct's carriers cluster by grammatical family against a matched null — §4.6, and §4.8 artefact 3 reads the layer of largest response from the same file.
validation/paper1/PROBE.json 4 probe_margins.py the probe in full (Appendix C.5): `rows.
validation/paper1/TABLE_B2.csv 4 - — not yet confirmed
validation/paper1/TWIN_CEILINGS.json 4 - — not yet confirmed
validation/paper2/B5_CHURN_VS_LEARNING.json 4 b5_churn.py across_layers.churn_vs_filling_change.spearman relates carrier change to how much the layer is still filling — §5's check that change is not a by-product of learning.
validation/r2/CURVE1_SPACING_anneal.json 4 step7.py the spacing dependence of curve 1 on the annealing branch, in the same bands as pretraining (per_band.<n>ref).
validation/r2/R2_REPORT.json 4 r2_report.py tie_break.n_modal_is_last_layer — the tie-break sensitivity §4.6 reports.
calibration/corpus.json 3 build_natural.py parsed = 253,398 — the reference corpus's parsed Python files, the declared stimulus distribution's base (Appendix A item 1).
validation/ablation/PLAN.json 3 ablation_full.py plan.total_construct_passes — the size of the removal experiment as planned (§A.1).
validation/paper2/ABLATION_STABLE.json 3 ablation_stable.py the same removal read with the mask count varied, so §3.3's effect can be shown not to depend on it (control_stability.<n>).
validation/paper2/B14_BANDS.json 3 b14_bands.py per_band.<cut>.band_size_first_ref is the size of the carrier set at each of the six cuts, and n_constructs_tested the 169 — §4.1's cut sensitivity.
inventory/inventory_v2.json 2 assign_tiers.py — not yet confirmed
validation/ablation/FULL_pretrain_iter_0484865.json 2 - — not yet confirmed
validation/paper1/FIG1_carriers_in_place.json 2 figure1_small.py the data behind Figure 2 (for's carriers in place), written beside the figure by figure1_small.py.
validation/paper1/SCOPE_OVERLAP.json 2 audit_recordings.py share_of_ceiling per construct at a reference — the convergence panel of Figure 4.
validation/paper1/YARDSTICK_coarse.json 2 b10.py twin_ceiling per construct under each yardstick alternative — the 0.747 C.3 quotes for the checkpoint's health.
validation/paper2/B12_TWIN_TURNOVER.json 2 b12_twin_turnover.py per_reference.<ref>.twin_overlap_median and twin_turnover_median are the agreement between the two twins at one checkpoint, which is the instrument's own noise — §3.1's 0.84 and 0.16. It stores no minimum; see §Settled while tracing.
validation/paper2/B2_ANNEAL_DROP.json 2 b2_anneal_drop.py the annealing branch read on the same series as pretraining; forced.n_series and the per-series thresholds are §3.5's counts.
validation/paper2/C2_PYTHIA_TWIN.json 2 c2_pythia_twin.py the second model: carrier_overlap per construct and opencoder_comparison.carrier_overlap_last_checkpoint put Pythia's twin agreement beside OpenCoder's (§6).
validation/paper2/COOCCURRENCE.json 2 cooccurrence.py pairs_total = 14,196 — all construct pairs, the denominator of §4.7's sharing figures.
validation/paper2/LICENCE_TABLES.json 2 licence_tables.py — not yet confirmed
validation/paper2/RATE_READINGS.json 2 rate_readings.py primary.<cut>.<window>[].median_excess is the carrier change over a fixed gap, beyond the twin turnover, read against its own ceiling — §4.1's quantity. §4.1 reads primary.carrier5; definition_1_primary holds the declared windows and the R² floor.
validation/r2/CURVE1_SPACING_pretrain.json 2 step4_flat.py the spacing dependence that C.3 corrects for: spacing_dependence.n_pairs is the 1,404 point–partner pairs, and the per_band keys are the four declared bands.
calibration/identifiers.json 1 - a calibration table of identifier draw rates. It carries no quantity the paper names; every row pointing here is weak — the value index offered it for a token count such as '84 billion' and no field name tied anything to the sentence. Not a source for any number in paper 2.
calibration/vocabulary.json 1 count_vocabulary.py a generator calibration table; no quantity the paper names. Rows pointing here are weak.
validation/paper1/C3_YARDSTICK_NATS.json 1 c3_yardstick_nats.py paper 1's yardstick sensitivity, cited in paper 2's §4.8 limitation ('the turnover moves by 0.003–0.005').
validation/paper1/YARDSTICK_iv_cells.json 1 b9_b10.py the 20-cell yardstick's own cells (4 token classes x 5 fifths) and their occupancy.
validation/paper2/A38_POPULATION.json 1 - the population the readings are taken over — 35 pretraining references and the declared partner-factor band.
validation/paper2/B10_SPACING_ADJUSTED.json 1 b10_fit.py the withdrawn fitted form, kept because D.1 artefact 4 reports what it would have given; per_start.<iter>.n_points are its pair counts.
validation/paper2/B17B_RETURN_SPLIT.json 1 b17b_return_split.py arms.fell_{beyond,within}_one_twin_unit.{departures,lift,lift_ci95} split every departure by whether the neuron's entry fell by more than its twin difference, and give the return rate over the matched control — §4.2's return result. share_of_departures_beyond_one_twin_unit is the 92.5%.
validation/paper2/B6_PERLAYER_SHARING.json 1 b6_perlayer.py occupancy_by_layer and per_layer.<n>.trend_spearman_vs_log_step are where in the network the carriers sit and whether that moves (§4.6).
validation/paper2/CEILINGS_PAIRWISE.json 1 - the cross-checkpoint ceiling — chance agreement between different constructs with one profile at each end of the pair, which is the quantity the excess is read against.
validation/paper2/CORE_TOKENS.json 1 core_tokens.py which token pieces each construct's core realises — the strict subset §A.3 reads the zero floor on.
validation/paper2/TBC22_SHARES.json 1 tbc22_shares.py cuts.<cut>.share_of_ceiling — the change normalised by each cut's own ceiling, §4.1's 0.925–0.964.
validation/r2/R2_CURVE4.json 1 r2_curve4.py curve 4, the loss curve, per series and per piece (level_first, level_last, noise_unit).
validation/r2/STEP7_pretrain.json 1 step7.py the bend analysis: whether a series bends at a common date across constructs (§4.1, C.3).

Every number, by paragraph

¶6. A neuron's activation at the construct's position mixes several sources. How is the part due to the construct's role separated from the rest? The read…

number mark file field script
0.5 declared — illustrative: 'a raw difference of 0.5 is large for one neuron and nothing for another'. Part of the argument for the yardstick, not a reading. —
3 declared — illustrative: 'one may sit near 0 and another near 3'. —
0 declared — illustrative: 'one may sit near 0 and another near 3'. The argument for the yardstick, not a reading. —

¶7. In what unit should a neuron's response be stated, so that neurons with different ordinary levels and spreads can be compared? In the neuron's own ord…

number mark file field script
2 declared — illustrative: 'an entry of 2 says this neuron responds by two of its ordinary spreads'. Part of the definition. —

¶10. The two nulls follow the corruption check of \citet{oikarinen2025} and the random-set null of \citet{kim2018}, applied to an instrument rather than to…

number mark file field script
7 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.With.old_set.n_random_below ablation_ranks.py

¶13. 2. Sparsity — the share of the squared norm in the largest 5% of entries, on the standardised form: how concentrated the response is.…

number mark file field script
5 count validation/r2/STEP7_pretrain.json p9.beside_it_a34.n_sparsity_first step7.py

¶15. 4. The carrier set — the 5% of neurons with the largest standardised entries. Two random 5% sets overlap by 0.05.…

number mark file field script
0.05 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.per_construct.ListComp.old_set_over_random_nats ablation_nats.py
5 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.With.old_set.n_random_at_or_above ablation_ranks.py

¶17. The baseline is the same architecture with random weights, read with the same battery: whatever it gives is what the battery and the architecture give…

number mark file field script
0.20 key validation/paper2/B17B_RETURN_SPLIT.json arms.fell_beyond_one_twin_unit.control_rate b17b_return_split.py

¶18. The inventory: the whole language. The constructs are not a chosen sample: every node of Python 3.12's grammar that appears as text of its own, and …

number mark file field script
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
143 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.ImportFrom.current.n_random_at_or_above ablation_ranks.py
206 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.NamedExpr.current.n_random_at_or_above ablation_ranks.py
63 count validation/r2/STEP3_SENSES_pretrain.json `second_sense.with_pilot product

¶19. The battery. OpenCoder's training data was not released, so a public corpus of 253,398 parsed Python files is the reference corpus, and its rates ar…

number mark file field script
253,398 key calibration/corpus.json parsed build_natural.py
1,280 canon validation/paper1/CORE_COUNTS.json max_family_size — the largest core family core_counts.py
1,440 key validation/paper2/CORE_TOKENS.json constructs.AnnAssign.n_core_spans_per_side core_tokens.py
720 derived validation/paper1/CORE_COUNTS.json 8 cores x 90 cells — the sentence gives the arithmetic: 8 x 90 = 720 prompts a set. core_counts.py
210 canon validation/paper1/CORE_COUNTS.json median_family_size — the median size of a construct's core family core_counts.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
42 canon validation/paper1/CORE_COUNTS.json min_family_size — the smallest core family core_counts.py

¶20. The read site and its gate. The read site is the first token of the construct's node: on for x in range(n): the token for; for a call to len t…

number mark file field script
0.056 key validation/paper1/RECHECK_PER_PROMPT.json `rows.untrained ResourceWarning.2 convergence.curve[2].cosine_sd`
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
80 count validation/ablation/PLAN.json plan.total_construct_passes ablation_full.py

¶21. Artefact: the battery in full — the prompts of A and B for all 188 constructs in both twins, the set C, set A regenerated for every construct from a…

number mark file field script
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py

¶22. The model and its neurons. OpenCoder-1.5B \citep{huang2024} has 24 layers with an MLP hidden width of 6,144 (SwiGLU). Each MLP block's hidden layer …

number mark file field script
147,456 canon validation/r2/STEP8_GRAPH_pretrain.json n_units — the product space, 24 layers x 6,144 neurons -
6,144 key validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.tensors.model.layers.12.mlp.gate_proj.weight.shape[0] b16b_weight_norms.py
24 count validation/paper2/B5_CHURN_VS_LEARNING.json across_layers.churn_vs_filling_change.n b5_churn.py

¶23. The references. Sixty-one references were shown the battery: 35 pretraining checkpoints (the twenty from 4.19 to 83.9 billion tokens, then fifteen s…

number mark file field script
1.25 declared calibration/checkpoints.json all[].step (the schedule's spacing) — the declared spacing of the fifteen tail references, x1.25 in tokens; the steps themselves are stored. checkpoint_inventory.py
4.19 value validation/paper2/B12_TWIN_TURNOVER.json between_checkpoints.per_pair[0].from_tokens_b b12_twin_turnover.py
83.9 derived calibration/checkpoints.json all[].step = 20,000 — 20,000 x 4,194,304 tokens/step = 83,886,080,000 = 83.9 billion. The same conversion gives every token figure in both papers. checkpoint_inventory.py
2.03 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0484865.tokens_b = 2,033.67 — 2.03 trillion tokens is this reference, iteration 484865 ceilings.py
35 count validation/paper2/A38_POPULATION.json n_pretraining_references -
24 count validation/paper2/B2_ANNEAL_DROP.json n_anneal_references b2_anneal_drop.py

¶24. What is stored per prompt. The per-core means are enough for every reading in §4 and for checks 1, 4, 5 and 8. Single-prompt activations, which chec…

number mark file field script
20,000 key calibration/checkpoints.json all[14].step checkpoint_inventory.py
1,000 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.iter b16b_weight_norms.py
164 count validation/paper1/PROBE_MARGINS.json per_reference.untrained.n_constructs probe_margins.py
31 count validation/paper1/PROBE.json hidden_unit_population.n probe_margins.py
7 count validation/paper1/CHECK6_REWEIGHT.json per_construct.If.n_targets check6_reweight.py

¶25. Artefact: the record is not released in full; at 27.6 GB of accumulators a reference it comes to 2,022 GB. The dataset holds a worked example — twin…

number mark file field script
2,022 key validation/paper1/RECORD_SIZE.json total_GB = 2022.0 — the whole record over all 61 references, measured from the recording tree by record_size.py; the same figure is in record_GATE_111.json :: dataset_bytes_gb -
27.6 key validation/paper1/RECORD_SIZE.json accumulators_gb_per_reference = 27.69 — NEW ARTEFACT: before today this figure had no stored field anywhere. Written by experiments/record_size.py (not CPU-only: it reads the dataset tree). -
272 derived — the release tree itself, checked against the file sizes — the three record files at tag v1: twin1__C_cells.npz 142.9 MB, twin1__For_B_acc.npz 89.0 MB, twin1__For_A_acc.npz 39.7 MB = 271.6 MB, printed 272. Not a stored field: it is the size of what the release carries, so it is checked against the tree as the battery's 78 MB is. —
1 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.old_set.n_exceeding_every_mask ablation_ranks.py

¶26. The cells. A kind of position (§2.3) is here a cell, defined by two properties of a position: the class of the token at it — keyword, identifier, …

number mark file field script
147,456 canon validation/r2/STEP8_GRAPH_pretrain.json n_units — the product space, 24 layers x 6,144 neurons -
2.95 key validation/paper1/CHECK6_REWEIGHT.json summary.shift_in_twin_units.For = 2.953 — how far re-weighting B to A's companion shares moves the profile, in twin units, for for. check6_reweight.py
2.3 declared — a cross-reference, '\S2.3', written with the LaTeX escape rather than the § sign, which is why the cleaner first let it through. Not a quantity. —
313 canon validation/paper1/LENGTHS.json by_set_kind.ALL.max — the longest prompt in the battery, in tokens atlas.py
20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py
2 derived validation/r2/STEP8_GRAPH_pretrain.json n_units = 147,456 — 20 x 147,456 = 2,949,120 yardstick entries; the sentence gives the arithmetic. -

¶27. From the record to a profile. (1) On set C's part of the record, for each neuron and each of the 20 cells, the mean μ₀ and spread σ₀ of the activati…

number mark file field script
7,373 canon validation/paper2/B14_BANDS.json per_band.q5pct.band_size_first_ref — the 5% cut's carrier-set size, 5% of 24 x 6,144 b14_bands.py
20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py

¶28. Artefact: the carrier sets of every construct at all 61 references, with the twin ceilings and the licence tables of Appendix B; and, as a worked ex…

number mark file field script
61 count validation/paper1/TWIN_CEILINGS.json n_references -
1 derived — the release tree itself: profiles/ holds one file — profiles/pretrain_iter_0484865/twin1/For.npz, 99.0 MB, 48 arrays -- the one profile the dataset carries, which is what the sentence says —

¶30. Check 4 is the reason the distribution is declared (§2.5): re-weighting the logged factors moves the profile by more than twice what redrawing the bat…

number mark file field script
0.008 value validation/paper2/ABLATION_STABLE.json per_reference.pretrain_iter_0001000.per_construct.AsyncFor.control_stability.200.change_from_half ablation_stable.py
2.95 key validation/paper1/CHECK6_REWEIGHT.json summary.shift_in_twin_units.For = 2.953 — how far re-weighting B to A's companion shares moves the profile, in twin units, for for. check6_reweight.py
5.50 key validation/paper1/CHECK6_REWEIGHT.json per_construct.With.shift_in_twin_units check6_reweight.py

¶31. The licence sentence: licensed on the gate — the two nulls passed on the 31 constructs they can run on — with these restrictions: the profile moves …

number mark file field script
2.95 key validation/paper1/CHECK6_REWEIGHT.json summary.shift_in_twin_units.For = 2.953 — how far re-weighting B to A's companion shares moves the profile, in twin units, for for. check6_reweight.py
2.34 key validation/paper1/CHECK4_RELATIVE.json per_construct[14].check4_twin_units check4_relative.py
5.50 key validation/paper1/CHECK6_REWEIGHT.json per_construct.With.shift_in_twin_units check6_reweight.py
33 count validation/paper1/CHECK6_COMPANIONS.json per_construct.ClassDef.n_companions check6_companions.py
31 count validation/paper2/LICENCE_TABLES.json layer_matched_real_norm.n_available licence_tables.py

¶32. How small a change in a construct's profile between two checkpoints can the record detect, and so how finely can it date a change? To the spacing of t…

number mark file field script
1,000 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.iter b16b_weight_norms.py
0.862 sibling validation/paper1/FIGURES.json check9.pairs.pretrain_iter_0020000.min_p1 — the same entry as min_p1, traced above atlas.py
0.918 value validation/paper1/FIGURES.json check9.pairs.anneal_iter_0002000.min_p1 atlas.py
8.56 value validation/paper1/FIGURES.json check9.pairs.pretrain_iter_0002000.median_p1 atlas.py
2.91 sibling validation/paper1/FIGURES.json check9.pairs.anneal_iter_0002000.median_p1 — the same entry as min_p1, traced above atlas.py
3.56 key validation/paper1/CHECK4_RELATIVE.json per_construct[176].check4_twin_units check4_relative.py
4.06 sibling validation/paper1/FIGURES.json check9.pairs.pretrain_iter_0484865.median_p1 — the same entry as min_p1, traced above atlas.py
2.4 FLAGGED validation/paper2/B10_SPACING_ADJUSTED.json median_per_1000_steps_dense = 0.00784, median_per_1000_steps_tail = 0.00666 — FLAG 6: Table D.1 sends '§4.2 resolution' to this artefact, whose dense/tail ratio is 1.18, not 2.4. The sentence 'early training moves the profile 2.4x further than late' is not reproduced by any field this trace could find. b10_fit.py

¶33. The same profile, read at 61 references, follows one construct from the first checkpoint to the end. For for, the raw norm ends at 52% of its first-…

number mark file field script
61 count validation/paper1/RECORD_SIZE.json n_references -
52 count validation/r2/STEP3_SENSES_pretrain.json `second_sense.with_pilot product

¶34. Does the choice of yardstick change which neurons are named? Yes: the yardstick is part of the measurement. Change what counts as ordinary at a positi…

number mark file field script
0.73 key validation/paper2/C2_PYTHIA_TWIN.json per_construct.tuple.carrier_overlap c2_pythia_twin.py
0.87 key validation/paper2/B14_BANDS.json per_band.abs1sd.twin_ceiling_first_ref b14_bands.py
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
167 derived validation/paper1/YARDSTICK_coarse.json summary.<alternative>.<reference>.share_below_ceiling — 'below the twin ceiling for 78 to 167 of the 169' is this share times 169, over the four coarser yardsticks; the shares are stored, the counts are not. b10.py
78 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0001000.per_construct.If.current.n_random_below ablation_ranks.py
20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py
31 count validation/paper1/LICENCE_TABLE_CORRECTED.json n_with_per_prompt_recheck licence_table.py

¶35. The unit also separates the model from the battery. Twin agreement, concept norm and carrier overlap with the previous reference are 0.981–0.989, 48.7…

number mark file field script
0.822 key record_GATE_111.json watched_ranges (and each reference's own manifest, watched) — one of the gate's three watched numbers: carrier overlap with the previous reference, lower end. The gate aborted a run when one fell out of band. -
0.989 key record_GATE_111.json watched_ranges (and each reference's own manifest, watched) — one of the gate's three watched numbers: twin agreement, upper end of the trained band. The gate aborted a run when one fell out of band. -
0.981 key validation/paper2/CEILINGS.json per_reference.pretrain_iter_0016000.cosine.twin_agreement ceilings.py
0.273 key record_GATE_111.json watched_ranges (and each reference's own manifest, watched) — one of the gate's three watched numbers: carrier overlap at the first untrained reference. The gate aborted a run when one fell out of band. -
0.710 value validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.per_construct.Lambda.carrier_rise_nats ablation_nats.py
0.717 key record_GATE_111.json watched_ranges (and each reference's own manifest, watched) — one of the gate's three watched numbers: twin agreement at the second untrained reference. The gate aborted a run when one fell out of band. -
0.286 value validation/paper1/RECHECK_PER_PROMPT.json `rows.untrained GeneratorExp.2 convergence.curve[1].cosine`
0.851 value validation/paper2/CEILINGS.json per_reference.pretrain_iter_0005000.abs3sd.twin_agreement ceilings.py
6.13 sibling validation/paper1/RECHECK_PER_PROMPT.json `rows.untrained GeneratorExp.7b null_split_half.p95_by_layer[3]` — the same entry as cosine, traced above
68.8 key record_GATE_111.json watched_ranges.trained_band_note — as above, the upper end. -
0.74 key validation/paper1/LICENCE_TABLE.json constructs.<c>.check1_twin_unit (the bootstrap arm) — the twin ceiling's core-bootstrap mean; the plug-in values, 0.28 and 0.84, are in the same block. licence_table.py
48.7 key record_GATE_111.json watched_ranges.trained_band_note ('every trained reference ~0.98 / 48-69 / 0.82-0.85') — the concept-norm band of the recording gate; the per-reference values are in each reference's own manifest under the watched key, in the record. -
0.84 key validation/paper1/TWIN_CEILINGS.json summary.product.pretrain_iter_0001000.median — the plug-in ceiling: the median over the 188 of twin 1's carrier set against twin 2's at that reference, in the product space. The core-bootstrap means beside it in the same sentence are LICENCE_TABLE.json's bootstrap arm. -
0.28 key validation/paper1/TWIN_CEILINGS.json summary.product.untrained.median — the plug-in ceiling: the median over the 188 of twin 1's carrier set against twin 2's at that reference, in the product space. The core-bootstrap means beside it in the same sentence are LICENCE_TABLE.json's bootstrap arm. -
0.21 key validation/paper1/LICENCE_TABLE.json constructs.<c>.check1_twin_unit (the bootstrap arm) — the twin ceiling's core-bootstrap mean, untrained; the plug-in values, 0.28 and 0.84, are in the same block. licence_table.py
6.34 key record_GATE_111.json watched_ranges (and each reference's own manifest, watched) — one of the gate's three watched numbers: the concept norm at the first untrained reference. The gate aborted a run when one fell out of band. -

¶36. Do the neurons the profile names as carriers affect the model's predictions at the construct's positions? Removing them raises the loss where the cons…

number mark file field script
0.088 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.median_vs_random_nats.hi ablation_nats.py
0.038 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.sign_test_rise_over_random.p ablation_nats.py
0.002 sibling validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.AsyncFor.control_mean_nats — the same entry as n_random_at_or_above, traced above ablation_ranks.py
2,034 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0484865.tokens_b = 2,033.67 — 2,034 b tokens is this reference, iteration 484865 ceilings.py
0.02 sibling validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.median_vs_random_nats.point — the same entry as hi, traced above ablation_nats.py
0.14 sibling validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.median_rise_over_random_nats.hi — the same entry as point, traced above ablation_nats.py
0.40 sibling validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.SetComp.old_set.share_below — the same entry as n_random_at_or_above, traced above ablation_ranks.py
0.66 sibling validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.median_rise_over_random_nats.hi — the same entry as hi, traced above ablation_nats.py
1.40 key validation/ablation/FULL_pretrain_iter_0484865.json constructs.Lambda.baseline_nats = 1.4006 — the index skipped the _dl/ trees, which are artefact sources: Figure 1 and Table D.1 read them. The index now includes them. Try's 0.088 baseline is the same field at constructs.Try.baseline_nats = 0.0875. -
0.10 sibling validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.median_vs_random_nats.hi — the same entry as hi, traced above ablation_nats.py
83.9 derived calibration/checkpoints.json all[].step = 20,000 — 20,000 x 4,194,304 tokens/step = 83,886,080,000 = 83.9 billion. The same conversion gives every token figure in both papers. checkpoint_inventory.py
5.95 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.per_construct.Try.rise_over_random_nats ablation_nats.py
0.25 sibling validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.median_rise_over_random_nats.point — the same entry as hi, traced above ablation_nats.py
4.19 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0001000.tokens_b = 4.19 — 4.19 b tokens is this reference, iteration 1000 ceilings.py
0.06 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.median_rise_over_random_nats.point ablation_nats.py
0.03 sibling validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.per_construct.While.control_mean_nats — the same entry as rise_over_random_nats, traced above ablation_nats.py
0.70 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.per_construct.IfExp.old_set_over_random_nats ablation_nats.py
4.99 value validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.per_construct.Lambda.rise_over_random_nats ablation_nats.py
200 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.SetComp.old_set.n_random_at_or_above ablation_ranks.py
95 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.AsyncFor.old_set.n_random_below ablation_ranks.py
14 sibling validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.sign_test_rise_over_random.n_above_zero — the same entry as hi, traced above ablation_nats.py
16 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.median_vs_random_nats.n ablation_nats.py
12 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.sign_test_rise_over_random.n_above_zero ablation_nats.py
20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py

¶37. Do the neurons that carry for follow the token for, whatever its role, or the role of a loop, whatever its token? Neither: two roles of one token …

number mark file field script
147,456 canon validation/r2/STEP8_GRAPH_pretrain.json n_units — the product space, 24 layers x 6,144 neurons -
0.837 key validation/paper1/SCOPE_OVERLAP.json `rows.pretrain_iter_0484865 For.ceiling_within_scope_across_twins.module.overlap_share_of_K`
0.872 value validation/paper2/B18_RECURRENCE.json per_construct.len.twin_ceiling b18_recurrence.py
0.198 value validation/r2/R2_CURVE4.json `pieces.pretrain.series.For governed
0.494 key validation/paper1/SCOPE_OVERLAP.json `rows.pretrain_iter_0484865 For.between_scope_within_twin.twin1.overlap_share_of_K`
0.266 value validation/paper2/B6_PERLAYER_SHARING.json per_layer.23.share_last b6_perlayer.py
0.050 key validation/paper2/CEILINGS.json per_reference.pretrain_iter_0001000.carrier5.chance ceilings.py
0.850 value validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.NamedExpr.old_set.share_below ablation_ranks.py
0.250 value validation/paper2/ABLATION_STABLE.json per_reference.pretrain_iter_0020000.median_old_set_control_units ablation_stable.py
0.44 key validation/paper1/CHECK6_COMPANIONS.json per_construct.ClassDef.shares[22].a_nopad check6_companions.py
0.59 key validation/paper1/POOLED_SETS_45.json per_cut.6.categories.member_kind.builtin.purity pooled_sets_169.py
0.71 value validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.per_construct.Lambda.carrier_rise_nats ablation_nats.py
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
24 count validation/paper2/B5_CHURN_VS_LEARNING.json across_layers.churn_vs_filling_change.n b5_churn.py
5 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.With.old_set.n_random_at_or_above ablation_ranks.py

¶38. Figure 2. Where the for loop's carriers sit, at the end of pretraining (2,034 B tokens). (a) Carriers per unit of neurons, the neurons ordered b…

number mark file field script
2,034 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0484865.tokens_b = 2,033.67 — 2,034 b tokens is this reference, iteration 484865 ceilings.py
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
5 count validation/paper2/RATE_READINGS.json primary.carrier5.5k-10k[10].n_pairs rate_readings.py

¶39. When two constructs share carrier neurons, what do they have in common — a category of the inventory, or a place in the grammar? Their category in the…

number mark file field script
14,196 canon validation/paper2/COOCCURRENCE.json pairs_total — all construct pairs cooccurrence.py
1,000 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.iter b16b_weight_norms.py
32 count validation/paper1/POOLED_SETS_45.json per_cut.32.n_clusters_realised pooled_sets_169.py
2 count validation/paper2/RATE_READINGS.json primary.carrier5.5k-10k[13].n_pairs rate_readings.py

¶40. Can a linear probe, the field's default instrument, track a construct across checkpoints as the profile does? On a trained checkpoint it cannot, becau…

number mark file field script
0.998 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0004000.tensors.model.layers.12.mlp.gate_proj.weight.row_norm_q3 b16b_weight_norms.py
0.802 value validation/paper2/B18_RECURRENCE.json per_construct.EOFError.twin_ceiling b18_recurrence.py
0.999 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0005000.tensors.model.layers.12.mlp.up_proj.weight.row_norm_q1 b16b_weight_norms.py
0.653 key validation/paper1/PROBE.json `rows.untrained Ellipsis.probes.resid_2240
1.000 value validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.per_construct_ratio.n_excluded_control_mean_not_positive ablation_nats.py
0.902 key validation/paper1/PROBE.json `rows. .probes.
14.8 key validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0484865.median_mean_margin = 14.816 probe_margins.py
0.99 key validation/paper1/CHECK4_RELATIVE.json per_construct[8].check4_twin_units check4_relative.py
83.9 derived calibration/checkpoints.json all[].step = 20,000 — 20,000 x 4,194,304 tokens/step = 83,886,080,000 = 83.9 billion. The same conversion gives every token figure in both papers. checkpoint_inventory.py
13.8 key validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0001000.median_mean_margin = 13.825 probe_margins.py
16.5 key validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0020000.median_mean_margin = 16.501 probe_margins.py
4.19 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0001000.tokens_b = 4.19 — 4.19 b tokens is this reference, iteration 1000 ceilings.py
0.50 key validation/paper2/ABLATION_STABLE.json per_reference.pretrain_iter_0001000.per_construct.IfExp.effect_control_units ablation_stable.py
145 sibling validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0001000.n_at_ceiling — the same entry as median_mean_margin, traced above probe_margins.py
148 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.For.old_set.n_random_at_or_above ablation_ranks.py
164 count validation/paper1/PROBE_MARGINS.json per_reference.untrained.n_constructs probe_margins.py
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
24 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.ImportFrom.current.n_random_below ablation_ranks.py
31 count validation/paper1/PROBE.json hidden_unit_population.n probe_margins.py
84 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0020000.tokens_b = 83.89 — 84 b tokens is this reference, iteration 20000 ceilings.py
61 count validation/paper1/TWIN_CEILINGS.json n_references -

¶41. 1. The twin unit is too small for intervals. The two twins share their cores, so their disagreement measures the variation of surface details (names…

number mark file field script
150 derived validation/paper1/LICENCE_TABLE.json constructs.<c>.check1_twin_unit.median_disattenuated — 'above 1 for about 150 of 188' is a count over this per-construct field; the field is stored, the count is not. licence_table.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
1 count validation/paper2/B2_ANNEAL_DROP.json against_the_pretraining_floor.n_above_floor_by_more_than_one_unit b2_anneal_drop.py

¶42. 2. The standardised size grows while the real size shrinks. The yardstick's spread σ₀ shrinks over training, so the standardised norm rises for 144 …

number mark file field script
144 count validation/r2/STEP3_SENSES_pretrain.json `second_sense.without_pilot layer
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
148 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.For.old_set.n_random_at_or_above ablation_ranks.py

¶43. 3. The layer of largest response is unstable. Excluding the last layer moves it for 41% of constructs. Rule: comparisons are made in the product spa…

number mark file field script
147,456 canon validation/r2/STEP8_GRAPH_pretrain.json n_units — the product space, 24 layers x 6,144 neurons -
41 key validation/paper1/LENGTH_BAND_HELD.json summary.median_flagged_fall = 0.4114 — 'the flagged share by 41%'. band_held.py

¶47. 4. For comparisons across checkpoints, the smallest change it can resolve: the same units at every checkpoint and a measured resolution of 1,000 tra…

number mark file field script
1,000 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.iter b16b_weight_norms.py

¶48. Of this instance. What the choices of Table 3 cost on OpenCoder — the gate, length sensitivity, the mixture, the companions — is stated in §3.1 and …

number mark file field script
607 cited — Huang et al., 2024 (OpenCoder's pretraining corpus). Paper 2 quotes the same figure in its §4.8 limitation; see paper 2's Flag 4 about the missing citation there. —

¶49. 1. The inventory. Every entry of Python 3.12's grammar that appears as text, and every builtin name: 63 + 143 = 206 constructs. 188 were built; 18 w…

number mark file field script
206 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.NamedExpr.current.n_random_at_or_above ablation_ranks.py
143 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.ImportFrom.current.n_random_at_or_above ablation_ranks.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
18 count calibration/identifiers.json finance.detail.item_tax_rate.count -
63 count validation/r2/STEP3_SENSES_pretrain.json `second_sense.with_pilot product

¶50. 2. What the rule excludes. Of Python 3.12's grammar nodes, 48 never appear as text of their own, and are left out: module containers, context marker…

number mark file field script
48 count inventory/inventory_v2.json counts (the nodes left out) assign_tiers.py
63 count inventory/inventory_v2.json counts (the nodes that remain) assign_tiers.py

¶52. 4. The reference corpus. 253,398 parsed Python files. The written list of factors and rates drawn from it is ν, and ν's rule is that every property …

number mark file field script
253,398 value calibration/corpus.json parsed build_natural.py

¶53. 1. Sets A and B. 720 prompts per set in each twin, ninety from each of eight cores, for every one of the 188 constructs; a set across both twins is …

number mark file field script
1,440 derived validation/paper1/CORE_COUNTS.json 8 cores x 90 cells x 2 twins — 720 a set in each twin, so 1,440 across both. core_counts.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
720 count validation/paper2/B1_ENTROPY.json constructs.AnnAssign.roles.header_colon.n b1_entropy.py

¶54. 2. Cores. Drawn from a family whose size is the product of the construct's axes, from 42 (Starred) to 1,280 (For), median 210 (CORE_COUNTS.md)…

number mark file field script
1,280 canon validation/paper1/CORE_COUNTS.json max_family_size — the largest core family core_counts.py
210 canon validation/paper1/CORE_COUNTS.json median_family_size — the median size of a construct's core family core_counts.py
42 canon validation/paper1/CORE_COUNTS.json min_family_size — the smallest core family core_counts.py

¶55. 3. B's sub-sets. One per kind of out-of-role use — docstring, comment, string, identifier — and, for the 18 constructs whose token is shared with an…

number mark file field script
4,850 key validation/paper1/B_SUBTYPES.json subtype_totals (the other_role:sibling:* subtypes) — the sibling-B prompts, 1.8% of all B prompts. b_subtypes.py
1.8 derived validation/paper1/B_SUBTYPES.json subtype_totals (the other_role subtypes) over the B total — 4,850 sibling prompts as a share of all B prompts = 1.8%. b_subtypes.py
18 count validation/paper2/B5_CHURN_VS_LEARNING.json within_pair_across_constructs.n_pairs_positive b5_churn.py

¶56. 4. Set C. One pool for all constructs, generated from the same menus and the same formatter as A and B with no construct anchored in it, and longer:…

number mark file field script
97.7 key validation/paper1/LENGTHS.json by_set_kind.C.mean = 97.6735 — the search had required 'token' in the field's name; the field is simply mean under by_set_kind.C. atlas.py
56.9 key validation/paper1/LENGTHS.json by_set_kind.A.mean = 56.9403 — CORRECTION, as 97.7. atlas.py

¶58. 6. In all. 569,270 prompts and 33,271,350 tokens, 58.45 tokens per prompt (median 55, quartiles 28–81).…

number mark file field script
33,271,350 value validation/paper1/LENGTHS.json by_set_kind.ALL.total_tokens atlas.py
569,270 value validation/paper1/LENGTHS.json by_set_kind.ALL.n_prompts atlas.py
58.45 sibling validation/paper1/LENGTHS.json by_set_kind.ALL.mean — the same entry as total_tokens, traced above atlas.py
81 key validation/paper1/LENGTHS.json by_set_kind.ALL.q75 = 81 — prompt length in tokens over the whole battery. atlas.py
28 key validation/paper1/LENGTHS.json by_set_kind.ALL.q25 — prompt length in tokens. atlas.py
55 key validation/paper1/LENGTHS.json by_set_kind.ALL.median — prompt length in tokens. atlas.py

¶59. Four stages, each fixing one thing. (1) The core fixes the construct's own shape. A core is one combination of the construct's axes; for for the a…

number mark file field script
1,280 canon validation/paper1/CORE_COUNTS.json max_family_size — the largest core family core_counts.py
720 derived validation/paper1/CORE_COUNTS.json 8 cores x 90 cells — the sentence gives the arithmetic: 8 x 90 = 720 prompts a set. core_counts.py
90 count calibration/vocabulary.json vocabulary.attribute.finance.period_id.count count_vocabulary.py
3 declared — a figure caption's own count: three prompts are shown in Figure A.1. —
8 count validation/paper1/POOLED_SETS_45.json per_cut.2.categories.a_family.compound.n pooled_sets_169.py
2 count validation/paper2/B1_ENTROPY.json `dependent_slots.ImportFrom scope

¶60. Figure A.1. Three prompts from the for battery: core c3 drawn twice (module scope, e-commerce), and core c2 (module scope, biology). The shape i…

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3 declared — a figure caption's own count: three prompts are shown in Figure A.1 —
2 count validation/paper2/B1_ENTROPY.json `dependent_slots.ImportFrom scope

¶61. (4) Set B. B's prompts are built from their own shapes, which place the token in a docstring, a comment, a string or an identifier — and, for the 18…

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18 count validation/paper2/B5_CHURN_VS_LEARNING.json within_pair_across_constructs.n_pairs_positive b5_churn.py

¶64. (7) One asymmetry between A and B. A's grid is balanced by construction: 240 prompts per scope and 240 per padding level. B's is not: for for, 219…

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283 key validation/paper1/SET_GRIDS.json per_construct.For.B.by_padding.2 = 283 — NEW ARTEFACT. Written 5 Nov by experiments/backfill_paper1.py, which checks all four of section A.2's printed grids and refuses rather than write one that misses; b_subtypes.py now writes the same grids per construct. -
240 key validation/paper1/SET_GRIDS.json per_construct.For.A.A's grid: by_scope and by_padding all 240 — NEW ARTEFACT. Written 5 Nov by experiments/backfill_paper1.py, which checks all four of section A.2's printed grids and refuses rather than write one that misses; b_subtypes.py now writes the same grids per construct. -
219 key validation/paper1/SET_GRIDS.json per_construct.For.B.by_scope.module = 219 — NEW ARTEFACT. Written 5 Nov by experiments/backfill_paper1.py, which checks all four of section A.2's printed grids and refuses rather than write one that misses; b_subtypes.py now writes the same grids per construct. -
175 key validation/paper1/SET_GRIDS.json per_construct.For.B.by_padding.0 = 175 — NEW ARTEFACT. Written 5 Nov by experiments/backfill_paper1.py, which checks all four of section A.2's printed grids and refuses rather than write one that misses; b_subtypes.py now writes the same grids per construct. -
262 key validation/paper1/SET_GRIDS.json per_construct.For.B.by_padding.1 = 262 — NEW ARTEFACT. Written 5 Nov by experiments/backfill_paper1.py, which checks all four of section A.2's printed grids and refuses rather than write one that misses; b_subtypes.py now writes the same grids per construct. -
234 key validation/paper1/SET_GRIDS.json per_construct.For.B.by_scope.function = 234 — NEW ARTEFACT. Written 5 Nov by experiments/backfill_paper1.py, which checks all four of section A.2's printed grids and refuses rather than write one that misses; b_subtypes.py now writes the same grids per construct. -
267 key validation/paper1/SET_GRIDS.json per_construct.For.B.by_scope.method = 267 — NEW ARTEFACT. Written 5 Nov by experiments/backfill_paper1.py, which checks all four of section A.2's printed grids and refuses rather than write one that misses; b_subtypes.py now writes the same grids per construct. -

¶65. A construct is read only if its A and B prompts land on the same token piece in at least 80% of prompts, in both twins, on the indented scopes. Named …

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143 count validation/paper1/LOCATE_BY_CLASS.json by_contrast_class.named-builtin.depth.n atlas.py
25 count validation/paper1/LOCATE_BY_CLASS.json by_contrast_class.keyword-token.depth.n atlas.py
14 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.old_set.n_constructs_with_an_old_set ablation_nats.py
80 count validation/ablation/PLAN.json plan.total_construct_passes ablation_full.py
1 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.per_construct_ratio.n_excluded_control_mean_not_positive ablation_nats.py
5 count validation/paper1/B_SUBTYPES.json per_construct.Dict.n_subtypes b_subtypes.py

¶66. One MLP block of OpenCoder-1.5B. The residual stream (width 2,240) enters two trained projections, the gate (2,240 × 6,144) followed by the SiLU nonli…

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2,240 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.tensors.model.layers.12.mlp.gate_proj.weight.shape[1] b16b_weight_norms.py
6,144 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.tensors.model.layers.12.mlp.gate_proj.weight.shape[0] b16b_weight_norms.py

¶67. What is stored. Per reference, for every construct, both twins, every set and all 24 layers: per-core accumulators of the count and the mean raw act…

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2,022 key validation/paper1/RECORD_SIZE.json total_GB = 2022.04 — written 5 Nov by record_size.py; also record_GATE_111.json :: dataset_bytes_gb. -
27.6 key validation/paper1/RECORD_SIZE.json accumulators_gb_per_reference = 27.69 — the accumulator bytes over all 61 references divided by 61 -
107 key validation/paper1/RECORD_SIZE.json per_prompt_reference_gb = 107.27 — the largest reference; written 5 Nov by record_size.py. -
24 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.AsyncWith.old_set.n_random_at_or_above ablation_ranks.py

¶68. Per prompt. The 31 constructs with per-prompt MLP activations were drawn so that the checks that need them license the population that is read: 15 c…

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147 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.While.old_set.n_random_at_or_above ablation_ranks.py
890 derived validation/paper1/RECORD_SIZE.json per_prompt_split_GB['neurons (the per-prompt subset)'] = 146.72 — 146.72 x 188/31 = 889.8, printed 890. The draft adopted the measured basis of 5 Nov in place of the earlier 872, which rested on an unmeasured 144 GB. -
17 count validation/r2/STEP3_SENSES_pretrain.json `second_sense.with_pilot product
31 count validation/r2/CURVE1_SPACING_pretrain.json product.constructs.Pass.per_band.1.65-2.0.n step4_flat.py
15 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.per_construct_ratio.n_used ablation_nats.py

¶73. 5. Cells: token class × fifth of the prompt, 20 cells. Other splits are possible, under the two requirements of §3.3.…

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20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py

¶74. The checks of Table 4 at the final pretraining checkpoint (pretrain_iter_0484865, 2,034 B tokens); checks 2, 3, 7a and 7b after the re-run of 19 Oct…

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2,034 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0484865.tokens_b = 2,033.67 — 2,034 b tokens is this reference, iteration 484865 ceilings.py
7 count validation/paper1/CHECK6_REWEIGHT.json per_construct.If.n_targets check6_reweight.py

¶75. Table B.1. Each check over the constructs it ran on: the median, and the lowest and highest values with the constructs that hold them. The gate an…

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169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
31 count validation/paper1/LICENCE_TABLE_CORRECTED.json n_with_per_prompt_recheck licence_table.py
7 count validation/r2/CURVE1_SPACING_anneal.json layer.constructs.Pass.per_band.4ref.n_below_before step7.py

¶76. All 31 pass checks 7a and 7b.…

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31 count validation/r2/CURVE1_SPACING_pretrain.json product.constructs.Pass.per_band.1.65-2.0.n step4_flat.py
7 count validation/r2/CURVE1_SPACING_anneal.json layer.constructs.Pass.per_band.4ref.n_below_before step7.py

¶77. The gate. 19 constructs fail, with the share of prompts on one piece in brackets: AnnAssign (0.617), Assign (0.406), AsyncFunctionDef (0.518),…

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0.518 key validation/paper1/GATE_SHARES.json per_construct.AsyncFunctionDef.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.625 key validation/paper1/GATE_SHARES.json per_construct.BoolOp.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.617 key validation/paper1/GATE_SHARES.json per_construct.AnnAssign.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.995 derived validation/paper1/GATE_SHARES.json per_construct.<c>.min: the lowest among the 167 that pass, with NamedExpr (0.873) and Ellipsis (0.992) set aside, is 0.995833 — the sentence's floor, not a stored field; 13 constructs sit at it, the first of them ConnectionAbortedError -
0.250 key validation/paper1/GATE_SHARES.json per_construct.List.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.542 key validation/paper1/GATE_SHARES.json per_construct.Subscript.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.500 key validation/paper1/GATE_SHARES.json per_construct.Starred.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.992 key validation/paper1/GATE_SHARES.json per_construct.Ellipsis.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.406 key validation/paper1/GATE_SHARES.json per_construct.Assign.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.375 key validation/paper1/GATE_SHARES.json per_construct.UnaryOp.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.529 key validation/paper1/GATE_SHARES.json per_construct.ClassDef.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.873 key validation/paper1/GATE_SHARES.json per_construct.NamedExpr.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.503 key validation/paper1/GATE_SHARES.json per_construct.FunctionDef.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
0.371 key validation/paper1/GATE_SHARES.json per_construct.Tuple.min — the share of prompts whose A and B read sites land on the same token piece, the minimum over the four (twin, side) combinations stored beside it; the gate compares this against 0.80 -
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
19 count validation/paper1/GATE_SHARES.json n_fail -

¶78. Check 3. Eight statements have more than 5% of their neurons flagged as length-sensitive: With 55%, For 49%, If 47%, While 36%, ImportFrom…

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36 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.While.checks_corrected.check3_length.flagged_share licence_table.py
47 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.If.checks_corrected.check3_length.flagged_share licence_table.py
21 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Assert.checks_corrected.check3_length.flagged_share licence_table.py
55 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.With.checks_corrected.check3_length.flagged_share licence_table.py
49 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.For.checks_corrected.check3_length.flagged_share licence_table.py
10 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Delete.checks_corrected.check3_length.flagged_share licence_table.py
31 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ImportFrom.checks_corrected.check3_length.flagged_share licence_table.py
8 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Return.checks_corrected.check3_length.flagged_share licence_table.py
5 sibling validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Assert.checks_published.check2_convergence.n_points — the same entry as flagged_share, traced above licence_table.py

¶79. Check 4. Four constructs sit within one twin unit of their base profile: Global (0.71), UnaryOp (0.74), Continue (0.77), Attribute (0.99). T…

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0.74 key validation/paper1/CHECK4_RELATIVE.json per_construct[construct=UnaryOp].check4_twin_units check4_relative.py
0.99 key validation/paper1/CHECK4_RELATIVE.json per_construct[construct=Attribute].check4_twin_units check4_relative.py
0.77 key validation/paper1/CHECK4_RELATIVE.json per_construct[construct=Continue].check4_twin_units check4_relative.py
0.71 key validation/paper1/CHECK4_RELATIVE.json per_construct[construct=Global].check4_twin_units check4_relative.py

¶80. Check 5. 33 constructs have intervals understated by more than 1.5, 30 of them among the 169 read: NotImplemented 7.17, Exception 5.44, `Keyboar…

number mark file field script
2.86 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ListComp.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.97 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.AsyncFunctionDef.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.67 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.While.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.73 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Return.checks_published.check6_calibration.bootstrap_inflation licence_table.py
4.25 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.KeyboardInterrupt.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.47 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.DictComp.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.95 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Match.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.00 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ClassDef.checks_published.check6_calibration.bootstrap_inflation licence_table.py
3.68 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.PendingDeprecationWarning.checks_published.check6_calibration.bootstrap_inflation licence_table.py
3.24 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.IfExp.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.12 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.AsyncFor.checks_published.check6_calibration.bootstrap_inflation licence_table.py
7.17 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.NotImplemented.checks_published.check6_calibration.bootstrap_inflation licence_table.py
5.44 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Exception.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.77 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ascii.checks_published.check6_calibration.bootstrap_inflation licence_table.py
3.83 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.EnvironmentError.checks_published.check6_calibration.bootstrap_inflation licence_table.py
3.76 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ConnectionAbortedError.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.85 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.divmod.checks_published.check6_calibration.bootstrap_inflation licence_table.py
3.63 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ModuleNotFoundError.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.72 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.SetComp.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.68 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.memoryview.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.19 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.globals.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.75 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.FunctionDef.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.05 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.AsyncWith.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.92 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ord.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.09 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.iter.checks_published.check6_calibration.bootstrap_inflation licence_table.py
3.53 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ResourceWarning.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.03 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Assert.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.10 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.isinstance.checks_published.check6_calibration.bootstrap_inflation licence_table.py
2.20 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.Try.checks_published.check6_calibration.bootstrap_inflation licence_table.py
1.5 declared validation/paper1/LICENCE_TABLE_CORRECTED.json the threshold the sentence states, not a stored value — constructs above it are counted from checks_published.check6_calibration.bootstrap_inflation licence_table.py
169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
33 count validation/paper1/LICENCE_TABLE_CORRECTED.json count of constructs with checks_published.check6_calibration.bootstrap_inflation > 1.5 licence_table.py
30 count validation/paper1/LICENCE_TABLE_CORRECTED.json the same count restricted to constructs with in_p1 = true licence_table.py

¶82. Why two readings. The record does not keep the boundary between a prompt's padding and its core. Whole counts every line; pad-0 counts only the …

number mark file field script
0.980 key validation/paper1/CHECK6_COMPANIONS.json per_construct.Match.asymmetry_max.excl_audit_components_whole — the clause's two readings of Match's largest difference: the inventory's component list, which Table B.3 uses, and the generator's audit list check6_companions.py
0.186 key validation/paper1/CHECK6_COMPANIONS.json per_construct.Match.asymmetry_max.excl_inventory_components_whole — the clause's two readings of Match's largest difference: the inventory's component list, which Table B.3 uses, and the generator's audit list check6_companions.py
14 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.old_set.n_constructs_with_an_old_set ablation_nats.py
35 count validation/paper2/B18_RECURRENCE.json per_construct.set__builtin.b_configurations.n_clusters_within_one_twin_ceiling b18_recurrence.py
0 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.n_without ablation_nats.py

¶83. Where the difference comes from, and where it can be removed. Some of the difference is what the construct's grammar requires (every match case en…

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0.69 value validation/paper2/TBC22_SHARES.json cuts.q5pct.excess_ci95_raw[0] tbc22_shares.py

¶84. Which neurons are named, and why the re-weighting is not adopted. With's recorded and re-weighted carrier sets overlap by 0.77 at the final checkp…

number mark file field script
0.12 key validation/paper1/CHECK6_COMPANIONS.json summary.asymmetry_max.* / per_construct.<c> — the companion difference's range across the eight compound statements. check6_companions.py
0.13 key validation/paper1/CHECK6_COMPANIONS.json summary.asymmetry_max.* / per_construct.<c> — the companion difference's range across the eight compound statements. check6_companions.py
0.02 key validation/paper1/CHECK6_COMPANIONS.json summary.asymmetry_max.* / per_construct.<c> — the companion difference's range across the eight compound statements. check6_companions.py
0.92 key validation/paper2/B18_RECURRENCE.json per_construct.AsyncFor.twin_ceiling b18_recurrence.py
0.94 sibling validation/paper2/B18_RECURRENCE.json per_construct.AsyncFor.a_nearest_set.under_b10_model.A — the same entry as twin_ceiling, traced above b18_recurrence.py
0.05 key validation/paper2/B12_TWIN_TURNOVER.json untrained_reference.two_independent_5pct_sets_would_give b12_twin_turnover.py
0.77 key validation/paper2/C2_PYTHIA_TWIN.json per_construct.None.carrier_overlap c2_pythia_twin.py

¶85. Table B.3. Check 6, for the eight constructs: the concept norm at layer 12, and the asymmetry — as an L2 norm over all companions and as the large…

number mark file field script
12 count validation/r2/STEP3_SENSES_pretrain.json `second_sense.without_pilot layer
0 count validation/paper1/B_SUBTYPES.json per_construct.max.n_other_role_prompts b_subtypes.py

¶86. For the eight length-sensitive statements of B.2, padding is added before the construct, so it moves the read site to a later fifth of the prompt in 5…

number mark file field script
0.88 key validation/paper1/LENGTH_BAND_HELD.json constructs.ImportFrom.band_held.min_cos = 0.8841 — the low end of the band-held cosine range band_held.py
0.79 key validation/paper1/LENGTH_BAND_HELD.json constructs.With.as_measured.min_cos = 0.7878 band_held.py
0.99 key validation/paper1/LENGTH_BAND_HELD.json constructs.Return.band_held.min_cos = 0.9882 — the high end band_held.py
0.97 sibling validation/paper1/LENGTH_BAND_HELD.json constructs.With.band_held.min_cos = 0.9686 — the same construct's entry as the 0.79 above, with the band held band_held.py
19 key validation/paper1/LENGTH_BAND_HELD.json constructs.While.band_held.flagged_share = 0.1947 band_held.py
14 key validation/paper1/LENGTH_BAND_HELD.json constructs.Assert.band_held.flagged_share = 0.1377 band_held.py
41 key validation/paper1/LENGTH_BAND_HELD.json summary.median_flagged_fall = 0.4114 band_held.py
16 key validation/paper1/LENGTH_BAND_HELD.json constructs.ImportFrom.band_held.flagged_share = 0.1632 band_held.py
40 key validation/paper1/LENGTH_BAND_HELD.json constructs.With.band_held.flagged_share = 0.4025 band_held.py
26 key validation/paper1/LENGTH_BAND_HELD.json summary.median_index_fall = 0.2628 band_held.py
31 key validation/paper1/LENGTH_BAND_HELD.json constructs.If.band_held.flagged_share = 0.3120 band_held.py
98 key validation/paper1/LENGTH_BAND_HELD.json constructs.For.band_change_share = 0.9750 — the high end band_held.py
54 key validation/paper1/LENGTH_BAND_HELD.json constructs.Delete.band_change_share = 0.5375 — the low end of the band-change range over the eight band_held.py
5 declared validation/paper1/LENGTH_BAND_HELD.json check 3's own 5% threshold; Delete and Return fall below it at 0.0480 and 0.0256 band_held.py

¶87. Each yardstick names a carrier set per construct; the set is ablated and the loss rise is read over the mean of 20 size-matched random sets, in nats. …

number mark file field script
0.088 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.median_vs_random_nats.hi ablation_nats.py
5.95 key validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.per_construct.Try.rise_over_random_nats ablation_nats.py
20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py
16 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.sign_test_rise_over_random.n ablation_nats.py

¶88. Table C.1. Loss rise over the random mean, nats (constructs above, of 16).…

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16 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.median_rise_over_random_nats.n ablation_nats.py

¶89. The 20-cell split gives the lower effect at every checkpoint, as expected: it excludes neurons that are large only because of where they stand, and ab…

number mark file field script
200 count validation/ablation/FULL_pretrain_iter_0484865.json constructs.<c>.n_masks_reached = 200 -
20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py

¶90. Per construct. Taken one at a time against 320 random sets, 2 of 16 constructs exceed every random set at 4.19 B tokens, 8 at 84 B and 8 at the end,…

number mark file field script
4.19 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0001000.tokens_b = 4.19 — 4.19 b tokens is this reference, iteration 1000 ceilings.py
0.05 sibling validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.AsyncWith.carrier_rise_nats — the same entry as n_random_below, traced above ablation_ranks.py
321 derived validation/paper2/ABLATION_RANKS.json per_reference.*.n_masks = 320 — the floor 1/321 is 1/(n_masks + 1). ablation_ranks.py
320 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.Try.old_set.n_random_below ablation_ranks.py
84 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0020000.tokens_b = 83.89 — 84 b tokens is this reference, iteration 20000 ceilings.py
16 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.n_constructs_with_an_old_set ablation_nats.py
1 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0001000.per_construct_ratio.n_excluded_control_mean_not_positive ablation_nats.py
8 sibling validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.n_exceeding_every_mask — the same entry as n_random_below, traced above ablation_ranks.py
2 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0484865.old_set.n_without ablation_nats.py

¶91. Untrained, 4.19 B, 83.9 B and 2,034 B tokens. The running example's numbers over training, behind §4.2; the raw norm falls from 4.19 B on while the st…

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143.0 key validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0020000.norm_raw = 142.970 atlas.py
11.09 sibling validation/r2/R2_REPORT.json `curves.pretrain curve3_depth.dates.Global.untrained_value` — the same entry as untrained_value, traced above
0.427 key validation/paper1/FOR_EXAMPLE.json references.untrained.twin_agreement_cosine atlas.py
0.991 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0001000.twin_agreement_cosine — the same entry as norm_standardised, traced above atlas.py
0.505 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0484865.sparsity_standardised — the same entry as norm_standardised, traced above atlas.py
0.889 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0020000.twin_ceiling_plug_in — the same entry as norm_raw, traced above atlas.py
184.5 key validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0001000.norm_raw = 184.456 atlas.py
10.94 value validation/r2/R2_REPORT.json `curves.pretrain curve3_depth.dates.AsyncFor.untrained_value`
0.471 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0001000.sparsity_standardised — the same entry as norm_standardised, traced above atlas.py
11.89 sibling validation/r2/R2_REPORT.json `curves.pretrain curve3_depth.dates.len.level` — the same entry as untrained_value, traced above
0.390 value validation/paper1/FOR_EXAMPLE.json references.untrained.sparsity_standardised atlas.py
2,034 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0484865.tokens_b = 2,033.67 — 2,034 b tokens is this reference, iteration 484865 ceilings.py
0.538 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0020000.sparsity_standardised — the same entry as norm_raw, traced above atlas.py
251.5 key validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0484865.norm_standardised = 251.516 atlas.py
0.984 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0020000.twin_agreement_cosine — the same entry as norm_raw, traced above atlas.py
10.90 sibling validation/r2/R2_REPORT.json `curves.pretrain curve3_depth.dates.AsyncFor.untrained_value` — the same entry as untrained_value, traced above
270.9 key validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0020000.norm_standardised = 270.890 atlas.py
0.293 key validation/paper1/FOR_EXAMPLE.json references.untrained.twin_ceiling_plug_in atlas.py
0.872 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0484865.twin_ceiling_plug_in — the same entry as norm_standardised, traced above atlas.py
239.6 key validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0001000.norm_standardised = 239.561 atlas.py
0.902 sibling validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0001000.twin_ceiling_plug_in — the same entry as norm_standardised, traced above atlas.py
83.9 derived calibration/checkpoints.json all[].step = 20,000 — 20,000 x 4,194,304 tokens/step = 83,886,080,000 = 83.9 billion. The same conversion gives every token figure in both papers. checkpoint_inventory.py
30.2 key validation/paper1/FOR_EXAMPLE.json references.untrained.norm_standardised = 30.191 atlas.py
15.7 key validation/paper1/FOR_EXAMPLE.json references.untrained.norm_raw = 15.729 atlas.py
96.0 key validation/paper1/FOR_EXAMPLE.json references.pretrain_iter_0484865.norm_raw = 95.980 atlas.py
4.19 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0001000.tokens_b = 4.19 — 4.19 b tokens is this reference, iteration 1000 ceilings.py

¶92. In Figure C.1, all 24 × 6,144 MLP neurons of OpenCoder-1.5B drawn in place at the end of pretraining, one row per layer, the neurons within a layer or…

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6,144 key validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.tensors.model.layers.12.mlp.gate_proj.weight.shape[0] b16b_weight_norms.py
24 count validation/paper1/FIG1_carriers_in_place.json by_layer.n_layers figure1_small.py

¶93. Figure C.1. Panel (a): the for loop's carrier set, each carrier in the colour of its entry π(A) − π(B) in units of σ₀, every other neuron grey; …

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300 declared — a drawing choice: the inset of Figure C.1 enlarges the 300 highest-degree neurons. —
24 count validation/paper1/FIG1_carriers_in_place.json by_layer.n_layers figure1_small.py

¶94. What was clustered, and why. Two constructs share neurons when their carrier sets overlap. The question is whether the constructs that share most fa…

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14,196 canon validation/paper2/COOCCURRENCE.json pairs_total — all construct pairs cooccurrence.py
1,000 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0001000.iter b16b_weight_norms.py
32 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.While.current.n_random_at_or_above ablation_ranks.py
2 count validation/paper2/CEILINGS_PAIRWISE.json per_window.5k-10k[13].n_pairs -

¶95. Table C.2. Categories recovered by the clustering (p < 0.001 unless noted).…

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0.001 declared validation/paper1/FAMILIES.json permutations (1,000 label shuffles) — the declared significance threshold, p < 0.001 against 1,000 shuffles. atlas.py

¶96. Other readings. The highest-sharing pairs across categories are Delete–delattr (0.200) and Global–globals (0.094). Keyword tokens sit at a m…

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10.98 key validation/paper1/LOCATE_BY_CLASS.json by_contrast_class.keyword-token.depth.median atlas.py
0.673 key validation/paper1/LOCATE_BY_CLASS.json by_contrast_class['named-builtin'].sparsity.median = 0.6725 — as 11.97; the statements' 0.666 is the same field for the other class. atlas.py
11.97 key validation/paper1/LOCATE_BY_CLASS.json by_contrast_class['named-builtin'].depth.median = 11.9730 — an earlier search had read only the per-construct block; the class medians are in by_contrast_class. atlas.py
0.094 key validation/paper1/FAMILIES.json disagreements_top30[].jaccard — the family clustering's purity against its matched null. atlas.py
0.666 value validation/paper1/LOCATE_BY_CLASS.json by_contrast_class.keyword-token.sparsity.median atlas.py
0.200 value validation/paper2/B14_BANDS.json per_band.q1pct.median_kept_fraction_all_pairs b14_bands.py
189 count validation/paper1/POOLED_SETS_45.json multiplicity.n_tests pooled_sets_169.py
38 count validation/paper1/POOLED_SETS_45.json multiplicity.n_significant_after_holm pooled_sets_169.py
6 count validation/paper1/POOLED_SETS_45.json per_cut.6.n_clusters_realised pooled_sets_169.py
7 count validation/paper1/POOLED_SETS_45.json per_cut.2.categories.asdl_type.expr.n pooled_sets_169.py

¶97. The area under the curve: a median 1.000 at every trained reference, 145–148 of 164 constructs at or above 0.99. Two roles of one token (for as loop…

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1.000 key validation/paper1/FAMILIES.json per_cut.2.categories.builtin.purity = 1.0 — the family clustering's purity against its matched null. atlas.py
0.999 value validation/paper2/B16B_WEIGHT_NORMS.json per_checkpoint.pretrain_iter_0005000.tensors.model.layers.12.mlp.up_proj.weight.row_norm_q1 b16b_weight_norms.py
13.8 key validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0001000.median_mean_margin probe_margins.py
0.99 key validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.AsyncWith.old_set.share_below ablation_ranks.py
0.68 value validation/paper1/FAMILIES.json per_cut.16.categories.frame_class.requires loop.null_mean atlas.py
4.19 canon validation/paper2/CEILINGS.json per_reference.pretrain_iter_0001000.tokens_b = 4.19 — 4.19 b tokens is this reference, iteration 1000 ceilings.py
16.5 key validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0020000.median_mean_margin probe_margins.py
83.9 derived calibration/checkpoints.json all[].step = 20,000 — 20,000 x 4,194,304 tokens/step = 83,886,080,000 = 83.9 billion. The same conversion gives every token figure in both papers. checkpoint_inventory.py
14.8 key validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0484865.median_mean_margin probe_margins.py
0.75 key validation/paper1/YARDSTICK_coarse.json `rows. .alternatives..twin_ceiling` — the twin ceiling's untrained range, 0.68-0.75, over the coarser yardsticks.
148 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0484865.per_construct.For.old_set.n_random_at_or_above ablation_ranks.py
164 count validation/paper1/PROBE_MARGINS.json per_reference.untrained.n_constructs probe_margins.py
145 count validation/paper1/PROBE_MARGINS.json per_reference.pretrain_iter_0001000.n_at_ceiling probe_margins.py
128 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.If.old_set.n_random_at_or_above ablation_ranks.py
149 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0020000.per_construct.With.current.n_random_at_or_above ablation_ranks.py
3.2 key validation/paper1/PROBE_MARGINS.json per_reference.untrained.median_mean_margin = 3.2018 probe_margins.py
10 count validation/paper2/ABLATION_NATS.json per_reference.pretrain_iter_0020000.old_set.sign_test_vs_random.n_above_zero ablation_nats.py
7 count validation/paper1/C3_YARDSTICK_NATS.json per_reference.pretrain_iter_0001000.paired_differences.v_minus_one.sign_test.n_above_zero c3_yardstick_nats.py

¶98. Licence re-run. Four checks were re-run on 19 Oct 2026 after a fault in how per-prompt vectors were joined to their prompts was found and fixed (the…

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1.2142 unstored — the pre-re-run comparator. It comes from the superseded run the 19 Oct fix replaced, so no current artefact holds it -- which is expected, but it means the sentence's 'against 1.2142' cannot be checked from the release. —
0.7455 key validation/paper1/RECHECK_PER_PROMPT.json `rows.pretrain_iter_0484865 .'3 length'.index_median, median over the 31 = 0.7455` — an earlier search had looked for a summary field rather than for the median over the per-construct rows. The companion flagged share is the same block's flagged_share, median 0.0239 = 2.4%.
5.30 key validation/paper1/LICENCE_TABLE.json constructs.For.check8_nulls__suite_7.split_half.p95_norm licence_table.py
10.1 key validation/paper1/TABLE_B2.csv column '7a pub', median over the 31 — the scrambled margin as published; real norm over the null's p95 at layer 12. the figures of 5 Nov. -
0.99 key validation/paper1/LICENCE_TABLE.json constructs.AnnAssign.check1_twin_unit.median_cosine licence_table.py
4.57 key validation/paper1/RECHECK_PER_PROMPT.json `rows.pretrain_iter_0001000 Delete.7a null_scrambled.median_by_layer[8]`
6.13 sibling validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ImportFrom.checks_corrected.check8_nulls__suite_7.scrambled.p95_norm — the same entry as median_norm, traced above licence_table.py
10.7 key validation/paper1/TABLE_B2.csv column '7a cor', median over the 31 — the scrambled margin after the 19 Oct re-run; real norm over the null's p95 at layer 12. the figures of 5 Nov. -
5.27 key validation/paper1/RECHECK_PER_PROMPT.json `rows.pretrain_iter_0001000 NamedExpr.7a null_scrambled.p95_by_layer[20]`
12.8 key validation/paper1/TABLE_B2.csv column '7b cor', median over the 31 — the split-half margin after the re-run; real norm over the null's p95 at layer 12. the figures of 5 Nov. -
6.42 key validation/paper1/RECHECK_PER_PROMPT.json `rows.untrained DictComp.7b null_split_half.p95_by_layer[0]`
4.64 key validation/paper1/LICENCE_TABLE_CORRECTED.json constructs.ImportFrom.checks_corrected.check8_nulls__suite_7.split_half.median_norm licence_table.py
6.45 key validation/paper1/RECHECK_PER_PROMPT.json `rows.pretrain_iter_0001000 Assert.7a null_scrambled.p95_by_layer[13]`
4.86 key validation/paper1/LICENCE_TABLE.json constructs.Assert.check8_nulls__suite_7.scrambled.median_norm licence_table.py
4.5 derived validation/paper1/LICENCE_TABLE.json constructs.<c>.check8_nulls__suite_7.scrambled.p95_norm, against the corrected table — the scrambled null's p95 fell 6.42 -> 6.13, which is -4.5%. licence_table.py
9.6 key validation/paper1/TABLE_B2.csv column '7b pub', median over the 31 — the split-half margin as published; real norm over the null's p95 at layer 12. the figures of 5 Nov. -
3.9 FLAGGED — FLAG 7: the pre-re-run comparator, from the superseded run the 19 Oct 2026 fix replaced. No current artefact holds it, so Appendix D's claim that the re-run lowered two numbers cannot be checked from the release. The two re-run figures themselves ARE stored (see the 0.7455 and 2.4% rows). —
2.4 key validation/paper1/RECHECK_PER_PROMPT.json `rows.pretrain_iter_0484865 .'3 length'.flagged_share, median = 0.0239`
95 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0001000.per_construct.IfExp.current.n_random_at_or_above ablation_ranks.py
56 count validation/paper1/RECHECK_PER_PROMPT.json `rows.untrained Assert.2 convergence.curve[2].n`
31 count validation/paper2/LICENCE_TABLES.json layer_matched_real_norm.n_available licence_tables.py
18 sibling validation/r2/CURVE1_SPACING_anneal.json layer.constructs.BrokenPipeError.per_band.2ref.n_following — the same entry as n_following, traced above step7.py
12 count validation/r2/CURVE1_SPACING_anneal.json layer.constructs.Assert.per_band.8ref.n_following step7.py
20 key validation/paper1/LENGTH_BAND_HELD.json constructs.<c>.band_held.flagged_share — the band-held list ('six remain') is this field per construct; 20% is one of them (With 0.4025, For 0.31, If 0.31, While 0.20, ImportFrom 0.16, Assert 0.14). band_held.py
8 count validation/paper2/B1_ENTROPY.json against_the_model.n_governed_series b1_entropy.py

¶99. Check 4 in twin units. The licence table kept check 4's cosine and not its distance, so Table B.1's twin-unit row is rebuilt from both arms' per-cor…

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2.30 key validation/paper1/CHECK4_RELATIVE.json median_twin_units check4_relative.py
1.82 key validation/paper1/CHECK4_TWIN_UNITS.json quartiles[0] check4_twin_units.py
2.34 key validation/paper1/CHECK4_RELATIVE.json suite_median_7_Oct — the 7 October suite's median, the figure section 4.1 quotes check4_relative.py
18.6 key validation/paper1/CHECK4_TWIN_UNITS.json conversion_error_vs_stored_distance.max_relative = 0.18602 — the worst relative error of the chord identity against the stored distance, as a percentage; the construct is Slice check4_twin_units.py
2.25 key validation/paper1/CHECK4_TWIN_UNITS.json median_twin_units — the chord route: sqrt(2(1-cos)) from check 4's stored cosine check4_twin_units.py
3.49 key validation/paper1/CHECK4_TWIN_UNITS.json quartiles[1] check4_twin_units.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
90 derived validation/paper1/LICENCE_TABLE_CORRECTED.json sqrt(2(1-constructs.<c>.checks_published.check1_twin_unit.median_cosine)) / the same block's median_distance, minus 1, over the 188 — 170 of 188 = 0.904 are within 0.05, which the sentence prints as 90%; check 1 is the only check whose distance and cosine are both stored, which is why the identity is tested there licence_table.py
5 count validation/paper1/LICENCE_TABLE.json constructs.Assert.check2_convergence.n_points licence_table.py
4 count validation/paper1/CHECK4_RELATIVE.json n_within_one_twin_unit check4_relative.py
7 count validation/paper1/CHECK4_TWIN_UNITS.json n_within_one_twin_unit check4_twin_units.py

¶101. 2. Declare the distribution. List the factors around a construct (identifiers, literals, scope and nesting, companions, length, surrounding code) an…

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253,398 value calibration/corpus.json parsed build_natural.py

¶102. 3. Generate the battery. For each construct, set A (the construct in its role) and set B (its token out of role), the same companions in both, drawn…

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569,270 key validation/paper1/LENGTHS.json by_set_kind.ALL.n_prompts atlas.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
720 count validation/paper2/B1_ENTROPY.json constructs.AnnAssign.roles.header_colon.n b1_entropy.py

¶103. 4. Gate the read site. Keep a construct only if its A and B prompts put the read token on the same piece in at least 80% of prompts (Appendix A.4). …

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169 canon validation/paper2/B11_POWER.json n_constructs — the constructs that pass the read-site gate b11_power.py
188 canon validation/paper1/CORE_COUNTS.json n_constructs_built — the constructs the battery holds core_counts.py
80 count validation/ablation/PLAN.json plan.total_construct_passes ablation_full.py

¶104. 5. Record. Run the model on the battery at each checkpoint; store per-core means of every neuron's activation, with the cell axis kept, so the yards…

number mark file field script
164 count validation/paper1/PROBE_MARGINS.json per_reference.untrained.n_constructs probe_margins.py
36 count validation/paper1/CHECK6_COMPANIONS.json per_construct.While.n_companions check6_companions.py
43 count validation/r2/STEP3_SENSES_pretrain.json `second_sense.with_pilot product
28 key validation/paper1/RECORD_SIZE.json accumulators_gb_per_reference = 27.69 — written 5 Nov by record_size.py; 'about 28 GB of per-core means per reference'. -
31 count validation/paper1/LICENCE_TABLE_CORRECTED.json n_with_per_prompt_recheck licence_table.py
79 count validation/paper2/ABLATION_RANKS.json per_reference.pretrain_iter_0001000.per_construct.Import.current.n_random_at_or_above ablation_ranks.py
7 count validation/paper1/YARDSTICK_iv_cells.json `per_construct_reference.untrained Match.n_cells`