| # Noise ceiling + within-run correction (added 2026-08-25) |
|
|
| This directory is **additive**. It does not replace or correct any file elsewhere |
| in the dataset; the tables under `overall/`, `by-model/` and `diagnostics/` are |
| unchanged and still carry the run confound described in the top-level README. |
|
|
| What is new here is the measurement that was missing: a **noise ceiling**, and |
| alignment expressed as a fraction of it. |
|
|
| ## Why it matters |
|
|
| The top-level README says of the brain-alignment tables: *"these tables do not |
| show that language models align with the brain, and they do not show that they |
| fail to. The measurement cannot answer it."* That was correct for those tables. |
| With a ceiling, the question becomes answerable, and the answer is now a |
| **well-powered null** rather than an uninterpretable one. |
|
|
| ## The numbers |
|
|
| ds003604, task Phon, ses-5, 43 subjects, 72 stimuli (perceptual controls |
| excluded). Both RDMs are built from the *same* per-subject patterns and differ |
| only by the correction. |
|
|
| | | raw | within-run normalised | |
| |-----------------------------------|--------------|-----------------------| |
| | noise ceiling (LOO lower / upper) | 0.774 / 0.792| **0.849 / 0.859** | |
| | "different run" predicts dissimilarity | **+0.557** | **−0.041** | |
|
|
| Best layer per model against the corrected RDM: |
|
|
| | model | layer | Spearman rho | % of noise ceiling | |
| |---|---|---|---| |
| | beetle-humanscale-eng | 2 | +0.022 | **2.6%** | |
| | babylm-gpt2-3 | 5 | +0.013 | **1.5%** | |
| | pico-decoder-large | 0 | −0.001 | **−0.1%** | |
|
|
| **Read it this way.** Inter-subject reliability is 0.85 — well above the 0.2–0.4 |
| typical in this literature — so there is a large, replicable target available to |
| predict. Three models spanning three architectures capture 0–3% of it. |
|
|
| Two supporting points: |
|
|
| - **The ceiling rises after correction** (0.774 → 0.849). If the raw reliability |
| had been mostly the run artefact, removing the artefact would have *lowered* |
| the ceiling. It rose, so the correction removes noise rather than signal. |
| - **The corrected layer profile is sensible** — positive at early/middle layers, |
| negative at the output — whereas the raw profile is not. The correction makes |
| the measurement behave, and it still finds nothing. |
|
|
| ## Scope, stated plainly |
|
|
| One task × session cell, one session, 43 subjects. Whether this replicates across |
| all twelve cells is exactly what the full corrected sweep is running to answer; |
| those results will be added here as a separate, clearly-labelled set. Do not read |
| this single cell as the whole dataset. |
|
|
| ## Files |
|
|
| | file | what | |
| |---|---| |
| | `ceiling_Phon_ses-5.csv` | ceiling + run-confound, raw vs corrected | |
| | `alignment_vs_ceiling_Phon_ses-5.csv` | per model per layer, rsa raw/corrected and fraction of ceiling | |
| | `summary_Phon_ses-5.json` | the same as a single record | |
| | `fig_ceiling_layerwise.png/pdf` | alignment vs the ceiling band, per model, with a zoomed layer profile | |
| | `fig_ceiling_confound.png/pdf` | run confound and ceiling, before vs after correction | |
|
|
| ## Reproducing |
|
|
| ```bash |
| python scripts/ceiling_report.py --pattern-dir <patterns> --task Phon --session ses-5 |
| python scripts/make_ceiling_figures.py --dir paper_results/ceiling |
| ``` |
|
|
| Session RDMs built after 2026-08-25 carry their per-subject RDMs and a |
| `within_run_normalized` flag, so the ceiling is recomputable from the `.npz` |
| alone and a corrected RDM can never be confused with an uncorrected one. |
| `scripts/collect_ceilings.py` tabulates ceilings for a whole tree; |
| `scripts/verify_rdm_provenance.py` fails loudly on a tree with mixed provenance. |
|
|
