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@@ -5,7 +5,7 @@ tags: [model-merging, alignment, polypythia, goldfish, multilingual]
 
 # Compose-audit: putting the alignment map and the merging payoff on the SAME real models
 
-_Generated 2026-08-26 20:16 UTC · training-free · code: `/root/compose-audit` · operators/aligners/metrics imported unmodified from `mergeschool.core` (`/root/mergeability`, treated as read-only)._
+_Generated 2026-08-26 20:37 UTC · training-free · code: `/root/compose-audit` · operators/aligners/metrics imported unmodified from `mergeschool.core` (`/root/mergeability`, treated as read-only)._
 
 ## Read this first: what substrate, and what metric
 
@@ -20,7 +20,8 @@ _Generated 2026-08-26 20:16 UTC · training-free · code: `/root/compose-audit`
 > **Δfloor is a likelihood metric, not benchmark accuracy.** Nothing below shows that a likelihood
 > rescue transfers to BLiMP/MultiBLiMP accuracy, or to any downstream task. The audit's sharpest
 > point — *recovery is not success* — is **not** settled by these numbers and must not be written up
-> as if it were. No accuracy benchmark was run inside this window (see Coverage).
+> as if it were. **We tested that transfer directly on SET 1 with BLiMP — see the accuracy section
+> below — and it does not hold.** SET 4 has no accuracy benchmark in this window (see Coverage).
 
 
 ## SET 1 · PolyPythia seed-merge (the pure-coordinate ceiling)
@@ -41,30 +42,56 @@ C(9,2) = 36 seed pairs per size. Predictors are computed **before** any merge; t
 Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **34.14**, permutation-aligned **10.18** nats/token.
 
 
-### pythia-70m — 13 seed pairs · mean parent floor **3.606** nats/token · uniform-over-vocabulary reference **10.826** nats/token
+### pythia-31m — 36 seed pairs · mean parent floor **3.938** nats/token · uniform-over-vocabulary reference **10.826** nats/token
 
 | rung | n | mean nats/tok | mean Δfloor | median Δfloor | best Δfloor | beats naive | % of naive Δfloor removed |
 |---|---|---|---|---|---|---|---|
-| M0_naive_avg | 13 | 22.30 | 18.69 | 18.42 | 13.88 | 0/13 | 0.0% |
-| M1_perm_avg | 13 | 18.58 | 14.97 | 15.43 | 8.29 | 8/13 | 19.8% |
-| M1_orth_avg | 13 | 14.10 | 10.49 | 10.52 | 6.30 | 13/13 | 42.6% |
-| M2_task_arith | 13 | 83.87 | 80.27 | 80.48 | 45.14 | 0/13 | -331.8% |
-| M3_ties | 13 | 147.02 | 143.42 | 138.19 | 121.09 | 0/13 | -687.4% |
+| M0_naive_avg | 36 | 24.29 | 20.35 | 20.09 | 10.28 | 0/36 | 0.0% |
+| M1_perm_avg | 36 | 13.54 | 9.60 | 8.87 | 5.68 | 35/36 | 47.7% |
+| M1_orth_avg | 36 | 14.45 | 10.51 | 9.72 | 5.91 | 35/36 | 46.4% |
+| M2_task_arith | 36 | 97.24 | 93.30 | 89.81 | 46.94 | 0/36 | -366.7% |
+| M3_ties | 36 | 95.22 | 91.28 | 91.86 | 32.78 | 0/36 | -357.9% |
 
-Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **18.72**, permutation-aligned **14.95** nats/token.
+Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **20.30**, permutation-aligned **9.56** nats/token.
 
 
-### pythia-160m — 4 seed pairs · mean parent floor **3.260** nats/token · uniform-over-vocabulary reference **10.826** nats/token
+### pythia-70m — 34 seed pairs · mean parent floor **3.626** nats/token · uniform-over-vocabulary reference **10.826** nats/token
 
 | rung | n | mean nats/tok | mean Δfloor | median Δfloor | best Δfloor | beats naive | % of naive Δfloor removed |
 |---|---|---|---|---|---|---|---|
-| M0_naive_avg | 4 | 11.34 | 8.08 | 8.09 | 7.68 | 0/4 | 0.0% |
-| M1_perm_avg | 4 | 9.70 | 6.44 | 6.28 | 6.06 | 4/4 | 20.1% |
-| M1_orth_avg | 4 | 9.28 | 6.02 | 6.16 | 5.35 | 4/4 | 25.4% |
-| M2_task_arith | 4 | 31.20 | 27.94 | 27.65 | 22.30 | 0/4 | -245.3% |
-| M3_ties | 4 | 59.34 | 56.08 | 56.34 | 50.64 | 0/4 | -596.6% |
+| M0_naive_avg | 34 | 23.74 | 20.12 | 18.93 | 13.88 | 0/34 | 0.0% |
+| M1_perm_avg | 34 | 14.84 | 11.22 | 8.90 | 6.69 | 29/34 | 42.7% |
+| M1_orth_avg | 34 | 13.32 | 9.69 | 9.90 | 6.30 | 34/34 | 50.2% |
+| M2_task_arith | 34 | 95.16 | 91.53 | 90.58 | 45.14 | 0/34 | -358.7% |
+| M3_ties | 34 | 151.20 | 147.57 | 147.62 | 112.97 | 0/34 | -651.8% |
 
-Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **8.07**, permutation-aligned **6.43** nats/token.
+Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **20.12**, permutation-aligned **11.20** nats/token.
+
+
+### pythia-160m — 16 seed pairs · mean parent floor **3.255** nats/token · uniform-over-vocabulary reference **10.826** nats/token
+
+| rung | n | mean nats/tok | mean Δfloor | median Δfloor | best Δfloor | beats naive | % of naive Δfloor removed |
+|---|---|---|---|---|---|---|---|
+| M0_naive_avg | 16 | 11.81 | 8.56 | 8.25 | 6.88 | 0/16 | 0.0% |
+| M1_perm_avg | 16 | 9.93 | 6.67 | 6.36 | 5.50 | 14/16 | 20.9% |
+| M1_orth_avg | 16 | 9.53 | 6.28 | 6.16 | 5.16 | 16/16 | 26.1% |
+| M2_task_arith | 16 | 29.55 | 26.30 | 27.23 | 17.88 | 0/16 | -207.3% |
+| M3_ties | 16 | 60.17 | 56.92 | 56.80 | 49.98 | 0/16 | -573.4% |
+
+Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **8.55**, permutation-aligned **6.66** nats/token.
+
+
+### pythia-410m — 1 seed pairs · mean parent floor **2.967** nats/token · uniform-over-vocabulary reference **10.826** nats/token
+
+| rung | n | mean nats/tok | mean Δfloor | median Δfloor | best Δfloor | beats naive | % of naive Δfloor removed |
+|---|---|---|---|---|---|---|---|
+| M0_naive_avg | 1 | 9.16 | 6.19 | 6.19 | 6.19 | 0/1 | 0.0% |
+| M1_perm_avg | 1 | 8.61 | 5.64 | 5.64 | 5.64 | 1/1 | 8.9% |
+| M1_orth_avg | 1 | 8.77 | 5.81 | 5.81 | 5.81 | 1/1 | 6.2% |
+| M2_task_arith | 1 | 16.05 | 13.08 | 13.08 | 13.08 | 0/1 | -111.3% |
+| M3_ties | 1 | 13.13 | 10.17 | 10.17 | 10.17 | 0/1 | -64.2% |
+
+Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **6.19**, permutation-aligned **5.64** nats/token.
 
 
 **What this says.**
@@ -87,15 +114,67 @@ Linear-mode-connectivity barrier (`eval.merge_barrier`): naive **8.07**, permuta
    interior t that beats the better parent, aligned or not.
 
 
+### The scale trend — alignment's coordinate rescue WEAKENS with model size
+
+| substrate | n pairs | parent floor | naive Δfloor | rescue, permutation | rescue, Procrustes | rescue, best of the two | unaligned CKA | aligned CKA | weight coordinate share |
+|---|---|---|---|---|---|---|---|---|---|
+| pythia-14m | 36 | 4.38 | 32.43 | 69.9% | 50.5% | 72.0% | 0.588 | 0.374 | 0.0652 |
+| pythia-31m | 36 | 3.94 | 20.35 | 47.7% | 46.4% | 57.4% | 0.632 | 0.380 | 0.0645 |
+| pythia-70m | 34 | 3.63 | 20.12 | 42.7% | 50.2% | 54.5% | 0.673 | 0.432 | 0.0783 |
+| pythia-160m | 16 | 3.25 | 8.56 | 20.9% | 26.1% | 28.6% | 0.770 | 0.788 | 0.0936 |
+| pythia-410m | 1 | 2.97 | 6.19 | 8.9% | 6.2% | 8.9% | 0.309 | 0.183 | 0.0823 |
+
+The coordinator flagged this from the first two pairs and asked whether it survives the full grid.
+**It does, monotonically, across every size we ran.** The naive merge's Δfloor shrinks with scale
+*and* the share of it that alignment can remove shrinks faster. Two things are worth separating:
+
+- The **naive** merge gets less catastrophic with scale, which on its own would be an encouraging
+  trend for merging.
+- The **alignment rescue** shrinks at the same time. So the improvement at larger scale is not
+  something the coordinate story is buying; the coordinate-removable component of the obstruction is
+  a *decreasing* fraction of the total. Whatever is left over at 160m is not a coordinate problem,
+  and the same aligners that recover most of the 14m gap recover a quarter of it.
+
+That is a caution for the manuscript's central thesis, not a confirmation of it: alignment predicts
+and reduces the obstruction most where the obstruction matters least, and its purchase falls away in
+exactly the direction the field is scaling.
+
+
 ## SET 4 · Goldfish monolingual → bilingual merge (the real composition models)
 
-Uniform-over-vocabulary reference (a model that has learned nothing), mean over the two languages, in the same units: **eng-nld_Latn** 3.093 nats/byte.
+
+**Tokenizer diagnostic — read this before any SET 4 number.** The merged model lives in the *English* parent's token-id space, so partner-language text must be tokenized with the English tokenizer. It cannot represent much of that text:
+
+| text | UNK rate, English tokenizer | UNK rate, own tokenizer | bytes/token, English tok | bytes/token, own tok |
+|---|---|---|---|---|
+| eng_Latn | 0.1% | 0.1% | 4.92 | 4.92 |
+| nld_Latn | 0.3% | 0.1% | 2.71 | 5.09 |
+| spa_Latn | 5.3% | 0.1% | 2.83 | 5.01 |
+| ell_Grek | 46.5% | 0.0% | 5.73 | 8.92 |
+| pol_Latn | 11.4% | 0.0% | 2.24 | 5.15 |
+
+At a 46.5% UNK rate the English parent's *apparent* likelihood on Greek text is an artifact — it is confidently predicting `<unk>`, not modelling Greek — so it is not used as a floor. The partner-language floor below is the partner parent evaluated with its **own** tokenizer. The **English-side** column is the clean one (0.07% UNK) and is the primary SET 4 number.
+
+Uniform-over-vocabulary reference (a model that has learned nothing), mean over the two languages, in the same units: **eng-nld_Latn** 3.093, **eng-spa_Latn** 2.920, **eng-ell_Grek** 2.964, **eng-pol_Latn** 3.221 nats/byte.
+
+
+**PRIMARY — Δfloor on ENGLISH text vs the English parent (nats/UTF-8 byte).** This cell has no tokenizer artifact: the merge is asked only to retain what the English parent already had.
+
+| pair | M0_naive_avg | M1a_vocab_avg | M1b_vocab_perm_avg | M1c_vocab_orth_avg | M1d_vocab_perm_forced | M1e_vocab_orth_forced | M1f_perm_novocab |
+|---|---|---|---|---|---|---|---|
+| eng–nld_Latn | 0.889 | 1.056 | 1.058 | 1.058 | 1.167 | 0.990 | 0.891 |
+| eng–spa_Latn | 0.892 | 1.034 | 1.033 | 1.033 | 1.131 | 1.054 | 0.891 |
+| eng–ell_Grek | 0.983 | 1.054 | 1.054 | 1.054 | 1.080 | 1.041 | 0.983 |
+| eng–pol_Latn | 0.859 | 0.976 | 0.976 | 0.976 | 1.093 | 0.985 | 0.859 |
 
 **Δfloor vs the better parent, mean over the two languages, nats/UTF-8 byte** (lower is better; 0 would mean the merge matches the better parent):
 
-| pair | vocab overlap | floor eng | floor X | M0_naive_avg | M1a_vocab_avg | M1b_vocab_perm_avg | M1c_vocab_orth_avg | M1d_vocab_perm_forced | M1e_vocab_orth_forced | M1f_perm_novocab |
+| pair | vocab overlap | floor eng | floor X (own tok) | M0_naive_avg | M1a_vocab_avg | M1b_vocab_perm_avg | M1c_vocab_orth_avg | M1d_vocab_perm_forced | M1e_vocab_orth_forced | M1f_perm_novocab |
 |---|---|---|---|---|---|---|---|---|---|---|
 | eng–nld_Latn | 27.8% | 0.811 | 0.792 | 1.689 | 1.763 | 1.766 | 1.766 | 2.004 | 1.601 | 1.691 |
+| eng–spa_Latn | 23.1% | 0.811 | 0.746 | 1.643 | 1.637 | 1.635 | 1.635 | 1.831 | 1.632 | 1.643 |
+| eng–ell_Grek | 12.9% | 0.811 | 0.428 | 0.844 | 0.942 | 0.943 | 0.943 | 1.491 | 1.353 | 0.844 |
+| eng–pol_Latn | 15.5% | 0.811 | 0.799 | 1.789 | 1.687 | 1.687 | 1.687 | 2.065 | 1.656 | 1.789 |
 
 **Split by language, and Δ vs naive:**
 
@@ -108,6 +187,27 @@ Uniform-over-vocabulary reference (a model that has learned nothing), mean over
 | eng–nld_Latn | M1d_vocab_perm_forced | 1.167 | 2.840 | 0.314 |
 | eng–nld_Latn | M1e_vocab_orth_forced | 0.990 | 2.211 | -0.089 |
 | eng–nld_Latn | M1f_perm_novocab | 0.891 | 2.491 | 0.002 |
+| eng–spa_Latn | M0_naive_avg | 0.892 | 2.395 | 0.000 |
+| eng–spa_Latn | M1a_vocab_avg | 1.034 | 2.240 | -0.007 |
+| eng–spa_Latn | M1b_vocab_perm_avg | 1.033 | 2.238 | -0.008 |
+| eng–spa_Latn | M1c_vocab_orth_avg | 1.033 | 2.238 | -0.008 |
+| eng–spa_Latn | M1d_vocab_perm_forced | 1.131 | 2.531 | 0.187 |
+| eng–spa_Latn | M1e_vocab_orth_forced | 1.054 | 2.210 | -0.011 |
+| eng–spa_Latn | M1f_perm_novocab | 0.891 | 2.396 | -0.000 |
+| eng–ell_Grek | M0_naive_avg | 0.983 | 0.706 | 0.000 |
+| eng–ell_Grek | M1a_vocab_avg | 1.054 | 0.829 | 0.097 |
+| eng–ell_Grek | M1b_vocab_perm_avg | 1.054 | 0.831 | 0.098 |
+| eng–ell_Grek | M1c_vocab_orth_avg | 1.054 | 0.831 | 0.098 |
+| eng–ell_Grek | M1d_vocab_perm_forced | 1.080 | 1.901 | 0.646 |
+| eng–ell_Grek | M1e_vocab_orth_forced | 1.041 | 1.665 | 0.509 |
+| eng–ell_Grek | M1f_perm_novocab | 0.983 | 0.704 | -0.001 |
+| eng–pol_Latn | M0_naive_avg | 0.859 | 2.719 | 0.000 |
+| eng–pol_Latn | M1a_vocab_avg | 0.976 | 2.399 | -0.101 |
+| eng–pol_Latn | M1b_vocab_perm_avg | 0.976 | 2.399 | -0.101 |
+| eng–pol_Latn | M1c_vocab_orth_avg | 0.976 | 2.399 | -0.101 |
+| eng–pol_Latn | M1d_vocab_perm_forced | 1.093 | 3.037 | 0.276 |
+| eng–pol_Latn | M1e_vocab_orth_forced | 0.985 | 2.327 | -0.133 |
+| eng–pol_Latn | M1f_perm_novocab | 0.859 | 2.719 | 0.000 |
 
 **Rungs.** `M0_naive_avg` = straight weight average in raw index space (the merge the manuscript
 reports as failing). `M1a_vocab_avg` = English/partner embedding + unembedding rows transported into
@@ -120,60 +220,289 @@ block-normalised weight distance. `M1d/M1e` force the residual factor in regardl
 `M1f_perm_novocab` isolates the unit alignment with **no** vocabulary transport.
 
 
+## The accuracy test · does the likelihood rescue transfer? (BLiMP, SET 1)
+
+PolyPythia parents are English LMs, so BLiMP applies directly to SET 1's merges. Scoring is the standard minimal-pair comparison: total log p over the sentence, correct when the grammatical member scores higher. **Chance = 0.500.** Same merges, same alignment, same pairs as the Δfloor tables above.
+
+| substrate | n pairs | mean parent acc | better-parent ceiling | M0 naive | M1 permutation | M1 Procrustes | best rung, % of the parents' above-chance margin retained |
+|---|---|---|---|---|---|---|---|
+| pythia-14m | 36 | 0.652 | 0.664 | 0.518 | 0.533 | 0.530 | 28.5% |
+| pythia-70m | 9 | 0.722 | 0.729 | 0.526 | 0.542 | 0.541 | 21.6% |
+
+**This is the result the audit asked for, and it is negative.** On pythia-14m the permutation
+alignment removes ~70% of the naive merge's Δfloor in nats/token — and the merged model still scores
+near chance on BLiMP, against parents at ~0.66-0.69. A large, consistent, statistically obvious
+*likelihood* rescue buys essentially **no** grammatical competence back. "Recovery is not success"
+is not a caveat to add to a positive result here; on this substrate it is the result.
+
+
+Pair by pair, does the size of the likelihood rescue predict the size of the accuracy rescue? (Spearman, over seed pairs within a size.)
+
+| substrate | n | Spearman(Δfloor rescue, BLiMP rescue) | mean Δfloor rescue (nats/tok) | mean BLiMP rescue (acc) |
+|---|---|---|---|---|
+| pythia-14m | 36 | 0.139 | 23.44 | 0.0257 |
+| pythia-70m | 9 | -0.133 | 7.60 | 0.0209 |
+
 ## P0-2 · Do the pre-merge predictors predict the realised rescue?
 
 Outcome = **realised rescue** = the fraction of the naive Δfloor that the best M1 rung removes. Label = above the within-size median. Held out **by seed**: fold *k* is every pair touching seed *k*, trained on the pairs touching neither, so the predictor's sign (and, for the multivariate row, its coefficients) never see the held-out pairs. Null = **seed-cluster permutation** (2000 draws): permute the seed identities and re-map each pair's outcome to the permuted pair, leaving the predictor vector untouched — this preserves the pair-dependence structure that a plain label shuffle destroys. BH-corrected across the predictor family.
 
-| substrate | predictor | n | Spearman | AUROC (held out by seed) | null mean | perm p | BH q |
+| substrate | outcome | predictor | n | Spearman | AUROC (held out by seed) | null mean | perm p | BH q |
+|---|---|---|---|---|---|---|---|---|
+| pythia-14m | rescue_frac | weight_cosine | 36 | 0.095 | 0.549 | 0.501 | 0.316 | 0.491 |
+| pythia-14m | rescue_frac | weight_cosine_bn | 36 | 0.092 | 0.460 | 0.499 | 0.646 | 0.799 |
+| pythia-14m | rescue_frac | d_raw | 36 | -0.072 | 0.478 | 0.498 | 0.582 | 0.749 |
+| pythia-14m | rescue_frac | qmd_perm | 36 | 0.077 | 0.664 | 0.498 | 0.051 | 0.232 |
+| pythia-14m | rescue_frac | coord_share_perm | 36 | -0.074 | 0.438 | 0.500 | 0.735 | 0.821 |
+| pythia-14m | rescue_frac | qmd_orth | 36 | 0.093 | 0.676 | 0.497 | 0.037 | 0.232 |
+| pythia-14m | rescue_frac | coord_share_orth | 36 | -0.094 | 0.457 | 0.499 | 0.665 | 0.802 |
+| pythia-14m | rescue_frac | bnd_raw | 36 | -0.025 | 0.543 | 0.499 | 0.341 | 0.514 |
+| pythia-14m | rescue_frac | bnd_perm | 36 | 0.012 | 0.296 | 0.497 | 0.981 | 1.000 |
+| pythia-14m | rescue_frac | bnd_orth | 36 | 0.015 | 0.420 | 0.497 | 0.778 | 0.856 |
+| pythia-14m | rescue_frac | coord_share_bnd_perm | 36 | -0.009 | 0.478 | 0.503 | 0.596 | 0.755 |
+| pythia-14m | rescue_frac | coord_share_bnd_orth | 36 | -0.074 | 0.540 | 0.497 | 0.362 | 0.529 |
+| pythia-14m | rescue_frac | cka_mean | 36 | -0.013 | 0.605 | 0.499 | 0.151 | 0.371 |
+| pythia-14m | rescue_frac | cka_last | 36 | -0.478 | 0.651 | 0.499 | 0.067 | 0.253 |
+| pythia-14m | rescue_frac | qmd_act_perm | 36 | -0.207 | 0.657 | 0.500 | 0.055 | 0.232 |
+| pythia-14m | rescue_frac | qmd_act_procrustes | 36 | -0.207 | 0.657 | 0.500 | 0.055 | 0.232 |
+| pythia-14m | rescue_frac | qmd_act_ot | 36 | -0.050 | 0.568 | 0.501 | 0.255 | 0.448 |
+| pythia-14m | rescue_frac | task_vector_cosine | 36 | 0.131 | 0.580 | 0.498 | 0.223 | 0.414 |
+| pythia-14m | rescue_frac | MULTIVARIATE_ridge_all | 36 | 0.254 | 0.620 | 0.501 | 0.114 | 0.311 |
+| pythia-14m | dfloor_M1best | weight_cosine | 36 | 0.161 | 0.580 | 0.498 | 0.214 | 0.414 |
+| pythia-14m | dfloor_M1best | weight_cosine_bn | 36 | 0.075 | 0.528 | 0.501 | 0.405 | 0.570 |
+| pythia-14m | dfloor_M1best | d_raw | 36 | -0.244 | 0.639 | 0.497 | 0.106 | 0.298 |
+| pythia-14m | dfloor_M1best | qmd_perm | 36 | 0.383 | 0.698 | 0.496 | 0.047 | 0.232 |
+| pythia-14m | dfloor_M1best | coord_share_perm | 36 | -0.445 | 0.735 | 0.495 | 0.016 | 0.232 |
+| pythia-14m | dfloor_M1best | qmd_orth | 36 | 0.438 | 0.725 | 0.496 | 0.021 | 0.232 |
+| pythia-14m | dfloor_M1best | coord_share_orth | 36 | -0.457 | 0.738 | 0.495 | 0.015 | 0.232 |
+| pythia-14m | dfloor_M1best | bnd_raw | 36 | -0.102 | 0.318 | 0.501 | 0.961 | 1.000 |
+| pythia-14m | dfloor_M1best | bnd_perm | 36 | -0.002 | 0.222 | 0.502 | 0.997 | 1.000 |
+| pythia-14m | dfloor_M1best | bnd_orth | 36 | -0.000 | 0.204 | 0.502 | 1.000 | 1.000 |
+| pythia-14m | dfloor_M1best | coord_share_bnd_perm | 36 | -0.155 | 0.290 | 0.503 | 0.977 | 1.000 |
+| pythia-14m | dfloor_M1best | coord_share_bnd_orth | 36 | -0.206 | 0.593 | 0.498 | 0.210 | 0.414 |
+| pythia-14m | dfloor_M1best | cka_mean | 36 | 0.008 | 0.704 | 0.497 | 0.029 | 0.232 |
+| pythia-14m | dfloor_M1best | cka_last | 36 | -0.292 | 0.605 | 0.501 | 0.204 | 0.414 |
+| pythia-14m | dfloor_M1best | qmd_act_perm | 36 | -0.161 | 0.639 | 0.503 | 0.070 | 0.253 |
+| pythia-14m | dfloor_M1best | qmd_act_procrustes | 36 | -0.161 | 0.639 | 0.503 | 0.070 | 0.253 |
+| pythia-14m | dfloor_M1best | qmd_act_ot | 36 | -0.099 | 0.438 | 0.502 | 0.726 | 0.821 |
+| pythia-14m | dfloor_M1best | task_vector_cosine | 36 | 0.419 | 0.704 | 0.495 | 0.046 | 0.232 |
+| pythia-14m | dfloor_M1best | MULTIVARIATE_ridge_all | 36 | 0.539 | 0.778 | 0.497 | 0.003 | 0.228 |
+| pythia-160m | rescue_frac | weight_cosine | 15 | 0.364 | 0.714 | — | — | — |
+| pythia-160m | rescue_frac | weight_cosine_bn | 15 | 0.171 | 0.500 | — | — | — |
+| pythia-160m | rescue_frac | d_raw | 15 | -0.393 | 0.714 | — | — | — |
+| pythia-160m | rescue_frac | qmd_perm | 15 | -0.425 | 0.571 | — | — | — |
+| pythia-160m | rescue_frac | coord_share_perm | 15 | 0.371 | 0.554 | — | — | — |
+| pythia-160m | rescue_frac | qmd_orth | 15 | -0.450 | 0.554 | — | — | — |
+| pythia-160m | rescue_frac | coord_share_orth | 15 | 0.371 | 0.518 | — | — | — |
+| pythia-160m | rescue_frac | bnd_raw | 15 | -0.411 | 0.643 | — | — | — |
+| pythia-160m | rescue_frac | bnd_perm | 15 | -0.264 | 0.696 | — | — | — |
+| pythia-160m | rescue_frac | bnd_orth | 15 | -0.354 | 0.625 | — | — | — |
+| pythia-160m | rescue_frac | coord_share_bnd_perm | 15 | 0.211 | 0.696 | — | — | — |
+| pythia-160m | rescue_frac | coord_share_bnd_orth | 15 | 0.193 | 0.571 | — | — | — |
+| pythia-160m | rescue_frac | cka_mean | 15 | -0.121 | 0.571 | — | — | — |
+| pythia-160m | rescue_frac | cka_last | 15 | 0.364 | 0.696 | — | — | — |
+| pythia-160m | rescue_frac | qmd_act_perm | 15 | -0.079 | 0.214 | — | — | — |
+| pythia-160m | rescue_frac | qmd_act_procrustes | 15 | -0.079 | 0.214 | — | — | — |
+| pythia-160m | rescue_frac | qmd_act_ot | 15 | -0.111 | 0.232 | — | — | — |
+| pythia-160m | rescue_frac | task_vector_cosine | 15 | 0.357 | 0.696 | — | — | — |
+| pythia-160m | rescue_frac | MULTIVARIATE_ridge_all | 15 | 0.100 | 0.411 | — | — | — |
+| pythia-160m | dfloor_M1best | weight_cosine | 15 | -0.129 | 0.661 | — | — | — |
+| pythia-160m | dfloor_M1best | weight_cosine_bn | 15 | 0.064 | 0.393 | — | — | — |
+| pythia-160m | dfloor_M1best | d_raw | 15 | 0.161 | 0.375 | — | — | — |
+| pythia-160m | dfloor_M1best | qmd_perm | 15 | 0.161 | 0.679 | — | — | — |
+| pythia-160m | dfloor_M1best | coord_share_perm | 15 | -0.089 | 0.500 | — | — | — |
+| pythia-160m | dfloor_M1best | qmd_orth | 15 | 0.079 | 0.393 | — | — | — |
+| pythia-160m | dfloor_M1best | coord_share_orth | 15 | -0.046 | 0.339 | — | — | — |
+| pythia-160m | dfloor_M1best | bnd_raw | 15 | -0.507 | 0.589 | — | — | — |
+| pythia-160m | dfloor_M1best | bnd_perm | 15 | -0.636 | 0.696 | — | — | — |
+| pythia-160m | dfloor_M1best | bnd_orth | 15 | -0.482 | 0.571 | — | — | — |
+| pythia-160m | dfloor_M1best | coord_share_bnd_perm | 15 | 0.496 | 0.696 | — | — | — |
+| pythia-160m | dfloor_M1best | coord_share_bnd_orth | 15 | 0.314 | 0.518 | — | — | — |
+| pythia-160m | dfloor_M1best | cka_mean | 15 | -0.146 | 0.411 | — | — | — |
+| pythia-160m | dfloor_M1best | cka_last | 15 | 0.521 | 0.768 | — | — | — |
+| pythia-160m | dfloor_M1best | qmd_act_perm | 15 | -0.143 | 0.268 | — | — | — |
+| pythia-160m | dfloor_M1best | qmd_act_procrustes | 15 | -0.143 | 0.268 | — | — | — |
+| pythia-160m | dfloor_M1best | qmd_act_ot | 15 | -0.189 | 0.286 | — | — | — |
+| pythia-160m | dfloor_M1best | task_vector_cosine | 15 | 0.525 | 0.696 | — | — | — |
+| pythia-160m | dfloor_M1best | MULTIVARIATE_ridge_all | 15 | 0.507 | 0.679 | — | — | — |
+| pythia-31m | rescue_frac | weight_cosine | 36 | 0.274 | 0.704 | 0.504 | 0.029 | 0.232 |
+| pythia-31m | rescue_frac | weight_cosine_bn | 36 | 0.217 | 0.642 | 0.504 | 0.082 | 0.283 |
+| pythia-31m | rescue_frac | d_raw | 36 | -0.321 | 0.704 | 0.505 | 0.025 | 0.232 |
+| pythia-31m | rescue_frac | qmd_perm | 36 | -0.493 | 0.691 | 0.505 | 0.048 | 0.232 |
+| pythia-31m | rescue_frac | coord_share_perm | 36 | 0.460 | 0.654 | 0.505 | 0.095 | 0.298 |
+| pythia-31m | rescue_frac | qmd_orth | 36 | -0.405 | 0.562 | 0.503 | 0.284 | 0.450 |
+| pythia-31m | rescue_frac | coord_share_orth | 36 | 0.346 | 0.571 | 0.504 | 0.281 | 0.450 |
+| pythia-31m | rescue_frac | bnd_raw | 36 | -0.391 | 0.701 | 0.506 | 0.032 | 0.232 |
+| pythia-31m | rescue_frac | bnd_perm | 36 | -0.490 | 0.750 | 0.506 | 0.011 | 0.232 |
+| pythia-31m | rescue_frac | bnd_orth | 36 | -0.380 | 0.608 | 0.505 | 0.165 | 0.372 |
+| pythia-31m | rescue_frac | coord_share_bnd_perm | 36 | 0.427 | 0.710 | 0.505 | 0.025 | 0.232 |
+| pythia-31m | rescue_frac | coord_share_bnd_orth | 36 | 0.385 | 0.648 | 0.505 | 0.104 | 0.298 |
+| pythia-31m | rescue_frac | cka_mean | 36 | 0.100 | 0.546 | 0.503 | 0.345 | 0.514 |
+| pythia-31m | rescue_frac | cka_last | 36 | 0.039 | 0.380 | 0.499 | 0.877 | 0.939 |
+| pythia-31m | rescue_frac | qmd_act_perm | 36 | -0.060 | 0.444 | 0.500 | 0.722 | 0.821 |
+| pythia-31m | rescue_frac | qmd_act_procrustes | 36 | -0.060 | 0.444 | 0.500 | 0.722 | 0.821 |
+| pythia-31m | rescue_frac | qmd_act_ot | 36 | 0.010 | 0.401 | 0.501 | 0.841 | 0.913 |
+| pythia-31m | rescue_frac | task_vector_cosine | 36 | -0.123 | 0.481 | 0.499 | 0.577 | 0.749 |
+| pythia-31m | rescue_frac | MULTIVARIATE_ridge_all | 36 | 0.403 | 0.707 | 0.505 | 0.035 | 0.232 |
+| pythia-31m | dfloor_M1best | weight_cosine | 36 | -0.222 | 0.574 | 0.500 | 0.270 | 0.448 |
+| pythia-31m | dfloor_M1best | weight_cosine_bn | 36 | -0.084 | 0.605 | 0.497 | 0.144 | 0.365 |
+| pythia-31m | dfloor_M1best | d_raw | 36 | 0.234 | 0.593 | 0.500 | 0.222 | 0.414 |
+| pythia-31m | dfloor_M1best | qmd_perm | 36 | 0.243 | 0.633 | 0.503 | 0.166 | 0.372 |
+| pythia-31m | dfloor_M1best | coord_share_perm | 36 | -0.230 | 0.633 | 0.503 | 0.166 | 0.372 |
+| pythia-31m | dfloor_M1best | qmd_orth | 36 | 0.289 | 0.670 | 0.502 | 0.101 | 0.298 |
+| pythia-31m | dfloor_M1best | coord_share_orth | 36 | -0.271 | 0.670 | 0.503 | 0.103 | 0.298 |
+| pythia-31m | dfloor_M1best | bnd_raw | 36 | 0.163 | 0.633 | 0.503 | 0.132 | 0.346 |
+| pythia-31m | dfloor_M1best | bnd_perm | 36 | 0.105 | 0.577 | 0.503 | 0.260 | 0.448 |
+| pythia-31m | dfloor_M1best | bnd_orth | 36 | 0.114 | 0.611 | 0.501 | 0.186 | 0.405 |
+| pythia-31m | dfloor_M1best | coord_share_bnd_perm | 36 | -0.036 | 0.460 | 0.503 | 0.652 | 0.799 |
+| pythia-31m | dfloor_M1best | coord_share_bnd_orth | 36 | -0.011 | 0.534 | 0.500 | 0.393 | 0.564 |
+| pythia-31m | dfloor_M1best | cka_mean | 36 | 0.112 | 0.577 | 0.498 | 0.202 | 0.414 |
+| pythia-31m | dfloor_M1best | cka_last | 36 | -0.074 | 0.488 | 0.501 | 0.563 | 0.749 |
+| pythia-31m | dfloor_M1best | qmd_act_perm | 36 | 0.073 | 0.574 | 0.500 | 0.271 | 0.448 |
+| pythia-31m | dfloor_M1best | qmd_act_procrustes | 36 | 0.073 | 0.574 | 0.500 | 0.271 | 0.448 |
+| pythia-31m | dfloor_M1best | qmd_act_ot | 36 | 0.005 | 0.528 | 0.498 | 0.415 | 0.573 |
+| pythia-31m | dfloor_M1best | task_vector_cosine | 36 | 0.002 | 0.426 | 0.498 | 0.730 | 0.821 |
+| pythia-31m | dfloor_M1best | MULTIVARIATE_ridge_all | 36 | -0.111 | 0.500 | 0.501 | 0.516 | 0.701 |
+| pythia-70m | rescue_frac | weight_cosine | 33 | 0.096 | 0.357 | — | — | — |
+| pythia-70m | rescue_frac | weight_cosine_bn | 33 | -0.009 | 0.404 | — | — | — |
+| pythia-70m | rescue_frac | d_raw | 33 | 0.011 | 0.489 | — | — | — |
+| pythia-70m | rescue_frac | qmd_perm | 33 | -0.380 | 0.699 | — | — | — |
+| pythia-70m | rescue_frac | coord_share_perm | 33 | 0.389 | 0.728 | — | — | — |
+| pythia-70m | rescue_frac | qmd_orth | 33 | -0.415 | 0.691 | — | — | — |
+| pythia-70m | rescue_frac | coord_share_orth | 33 | 0.383 | 0.724 | — | — | — |
+| pythia-70m | rescue_frac | bnd_raw | 33 | -0.056 | 0.357 | — | — | — |
+| pythia-70m | rescue_frac | bnd_perm | 33 | -0.386 | 0.750 | — | — | — |
+| pythia-70m | rescue_frac | bnd_orth | 33 | -0.232 | 0.640 | — | — | — |
+| pythia-70m | rescue_frac | coord_share_bnd_perm | 33 | 0.444 | 0.768 | — | — | — |
+| pythia-70m | rescue_frac | coord_share_bnd_orth | 33 | 0.340 | 0.647 | — | — | — |
+| pythia-70m | rescue_frac | cka_mean | 33 | 0.499 | 0.702 | — | — | — |
+| pythia-70m | rescue_frac | cka_last | 33 | 0.464 | 0.688 | — | — | — |
+| pythia-70m | rescue_frac | qmd_act_perm | 33 | -0.498 | 0.724 | — | — | — |
+| pythia-70m | rescue_frac | qmd_act_procrustes | 33 | -0.498 | 0.724 | — | — | — |
+| pythia-70m | rescue_frac | qmd_act_ot | 33 | -0.474 | 0.721 | — | — | — |
+| pythia-70m | rescue_frac | task_vector_cosine | 33 | 0.068 | 0.596 | — | — | — |
+| pythia-70m | rescue_frac | MULTIVARIATE_ridge_all | 33 | 0.465 | 0.732 | — | — | — |
+| pythia-70m | dfloor_M1best | weight_cosine | 33 | 0.085 | 0.621 | — | — | — |
+| pythia-70m | dfloor_M1best | weight_cosine_bn | 33 | 0.005 | 0.607 | — | — | — |
+| pythia-70m | dfloor_M1best | d_raw | 33 | -0.067 | 0.445 | — | — | — |
+| pythia-70m | dfloor_M1best | qmd_perm | 33 | -0.379 | 0.636 | — | — | — |
+| pythia-70m | dfloor_M1best | coord_share_perm | 33 | 0.347 | 0.599 | — | — | — |
+| pythia-70m | dfloor_M1best | qmd_orth | 33 | -0.315 | 0.629 | — | — | — |
+| pythia-70m | dfloor_M1best | coord_share_orth | 33 | 0.245 | 0.544 | — | — | — |
+| pythia-70m | dfloor_M1best | bnd_raw | 33 | -0.156 | 0.585 | — | — | — |
+| pythia-70m | dfloor_M1best | bnd_perm | 33 | -0.467 | 0.728 | — | — | — |
+| pythia-70m | dfloor_M1best | bnd_orth | 33 | -0.233 | 0.651 | — | — | — |
+| pythia-70m | dfloor_M1best | coord_share_bnd_perm | 33 | 0.507 | 0.739 | — | — | — |
+| pythia-70m | dfloor_M1best | coord_share_bnd_orth | 33 | 0.295 | 0.673 | — | — | — |
+| pythia-70m | dfloor_M1best | cka_mean | 33 | 0.432 | 0.662 | — | — | — |
+| pythia-70m | dfloor_M1best | cka_last | 33 | 0.590 | 0.776 | — | — | — |
+| pythia-70m | dfloor_M1best | qmd_act_perm | 33 | -0.441 | 0.647 | — | — | — |
+| pythia-70m | dfloor_M1best | qmd_act_procrustes | 33 | -0.441 | 0.647 | — | — | — |
+| pythia-70m | dfloor_M1best | qmd_act_ot | 33 | -0.397 | 0.640 | — | — | — |
+| pythia-70m | dfloor_M1best | task_vector_cosine | 33 | 0.178 | 0.562 | — | — | — |
+| pythia-70m | dfloor_M1best | MULTIVARIATE_ridge_all | 33 | 0.388 | 0.647 | — | — | — |
+
+### Does a predictor fitted on one substrate transfer to another?
+
+Leave-one-**size**-out. Predictors are standardised *within* size first, so a predictor that only works by encoding which substrate it is looking at scores nothing. The sign (and the ridge coefficients) come from the other sizes only. Null = label permutation within the held-out substrate, 1000–2000 draws; BH across the whole transfer family.
+
+| predictor | outcome | held-out substrate | n | AUROC | null mean | perm p | BH q |
 |---|---|---|---|---|---|---|---|
-| pythia-14m | weight_cosine | 36 | 0.095 | 0.549 | 0.501 | 0.316 | 0.638 |
-| pythia-14m | weight_cosine_bn | 36 | 0.092 | 0.460 | 0.500 | 0.621 | 0.698 |
-| pythia-14m | d_raw | 36 | -0.072 | 0.478 | 0.499 | 0.596 | 0.692 |
-| pythia-14m | qmd_perm | 36 | 0.077 | 0.664 | 0.500 | 0.064 | 0.497 |
-| pythia-14m | coord_share_perm | 36 | -0.074 | 0.438 | 0.506 | 0.757 | 0.798 |
-| pythia-14m | qmd_orth | 36 | 0.093 | 0.676 | 0.499 | 0.040 | 0.497 |
-| pythia-14m | coord_share_orth | 36 | -0.094 | 0.457 | 0.501 | 0.674 | 0.735 |
-| pythia-14m | bnd_raw | 36 | -0.025 | 0.543 | 0.499 | 0.339 | 0.638 |
-| pythia-14m | bnd_perm | 36 | 0.012 | 0.296 | 0.499 | 0.978 | 0.978 |
-| pythia-14m | bnd_orth | 36 | 0.015 | 0.420 | 0.498 | 0.776 | 0.798 |
-| pythia-14m | coord_share_bnd_perm | 36 | -0.009 | 0.478 | 0.499 | 0.588 | 0.692 |
-| pythia-14m | coord_share_bnd_orth | 36 | -0.074 | 0.540 | 0.499 | 0.371 | 0.638 |
-| pythia-14m | cka_mean | 36 | -0.013 | 0.605 | 0.495 | 0.135 | 0.638 |
-| pythia-14m | cka_last | 36 | -0.478 | 0.651 | 0.501 | 0.069 | 0.497 |
-| pythia-14m | qmd_act_perm | 36 | -0.207 | 0.657 | 0.498 | 0.048 | 0.497 |
-| pythia-14m | qmd_act_procrustes | 36 | -0.207 | 0.657 | 0.497 | 0.046 | 0.497 |
-| pythia-14m | qmd_act_ot | 36 | -0.050 | 0.568 | 0.501 | 0.262 | 0.638 |
-| pythia-14m | task_vector_cosine | 36 | 0.131 | 0.580 | 0.500 | 0.223 | 0.638 |
-| pythia-14m | MULTIVARIATE_ridge_all | 36 | 0.254 | 0.620 | — | — | — |
-| pythia-70m | weight_cosine | 13 | 0.324 | 0.786 | 0.692 | 0.279 | 0.638 |
-| pythia-70m | weight_cosine_bn | 13 | -0.511 | 0.667 | 0.608 | 0.389 | 0.638 |
-| pythia-70m | d_raw | 13 | -0.297 | 0.619 | 0.570 | 0.400 | 0.638 |
-| pythia-70m | qmd_perm | 13 | -0.302 | 0.452 | 0.465 | 0.589 | 0.692 |
-| pythia-70m | coord_share_perm | 13 | 0.330 | 0.619 | 0.573 | 0.408 | 0.638 |
-| pythia-70m | qmd_orth | 13 | -0.604 | 0.714 | 0.635 | 0.357 | 0.638 |
-| pythia-70m | coord_share_orth | 13 | 0.560 | 0.738 | 0.654 | 0.297 | 0.638 |
-| pythia-70m | bnd_raw | 13 | 0.297 | 0.571 | 0.549 | 0.503 | 0.692 |
-| pythia-70m | bnd_perm | 13 | 0.055 | 0.524 | 0.522 | 0.572 | 0.692 |
-| pythia-70m | bnd_orth | 13 | -0.115 | 0.548 | 0.533 | 0.532 | 0.692 |
-| pythia-70m | coord_share_bnd_perm | 13 | 0.236 | 0.524 | 0.512 | 0.567 | 0.692 |
-| pythia-70m | coord_share_bnd_orth | 13 | 0.500 | 0.714 | 0.639 | 0.355 | 0.638 |
-| pythia-70m | cka_mean | 13 | 0.659 | 0.762 | 0.670 | 0.291 | 0.638 |
-| pythia-70m | cka_last | 13 | 0.500 | 0.762 | 0.674 | 0.311 | 0.638 |
-| pythia-70m | qmd_act_perm | 13 | -0.709 | 0.786 | 0.689 | 0.282 | 0.638 |
-| pythia-70m | qmd_act_procrustes | 13 | -0.709 | 0.786 | 0.687 | 0.289 | 0.638 |
-| pythia-70m | qmd_act_ot | 13 | -0.555 | 0.619 | 0.579 | 0.397 | 0.638 |
-| pythia-70m | task_vector_cosine | 13 | -0.038 | 0.548 | 0.534 | 0.519 | 0.692 |
-| pythia-70m | MULTIVARIATE_ridge_all | 13 | 0.099 | 0.405 | — | — | — |
+| MULTIVARIATE_ridge_all | rescue_frac | pythia-14m | 36 | 0.352 | 0.500 | 0.925 | 0.992 |
+| MULTIVARIATE_ridge_all | rescue_frac | pythia-160m | 15 | 0.571 | 0.496 | 0.346 | 0.630 |
+| MULTIVARIATE_ridge_all | rescue_frac | pythia-31m | 36 | 0.667 | 0.498 | 0.041 | 0.328 |
+| MULTIVARIATE_ridge_all | rescue_frac | pythia-70m | 33 | 0.559 | 0.502 | 0.291 | 0.583 |
+| coord_share_bnd_perm | rescue_frac | pythia-14m | 36 | 0.515 | 0.501 | 0.463 | 0.740 |
+| coord_share_bnd_perm | rescue_frac | pythia-160m | 15 | 0.696 | 0.497 | 0.130 | 0.400 |
+| coord_share_bnd_perm | rescue_frac | pythia-31m | 36 | 0.710 | 0.501 | 0.026 | 0.260 |
+| coord_share_bnd_perm | rescue_frac | pythia-70m | 33 | 0.768 | 0.502 | 0.005 | 0.140 |
+| qmd_act_perm | rescue_frac | pythia-14m | 36 | 0.657 | 0.501 | 0.067 | 0.344 |
+| qmd_act_perm | rescue_frac | pythia-160m | 15 | 0.429 | 0.500 | 0.693 | 0.977 |
+| qmd_act_perm | rescue_frac | pythia-31m | 36 | 0.525 | 0.497 | 0.387 | 0.672 |
+| qmd_act_perm | rescue_frac | pythia-70m | 33 | 0.724 | 0.495 | 0.007 | 0.140 |
+| cka_mean | rescue_frac | pythia-14m | 36 | 0.599 | 0.495 | 0.129 | 0.400 |
+| cka_mean | rescue_frac | pythia-160m | 15 | 0.304 | 0.502 | 0.915 | 0.992 |
+| cka_mean | rescue_frac | pythia-31m | 36 | 0.540 | 0.500 | 0.346 | 0.630 |
+| cka_mean | rescue_frac | pythia-70m | 33 | 0.298 | 0.497 | 0.972 | 0.992 |
+| weight_cosine | rescue_frac | pythia-14m | 36 | 0.580 | 0.506 | 0.242 | 0.566 |
+| weight_cosine | rescue_frac | pythia-160m | 15 | 0.714 | 0.505 | 0.081 | 0.344 |
+| weight_cosine | rescue_frac | pythia-31m | 36 | 0.704 | 0.500 | 0.018 | 0.240 |
+| weight_cosine | rescue_frac | pythia-70m | 33 | 0.467 | 0.496 | 0.627 | 0.962 |
+
+**SET 4, held out by language pair.** n = 4 language pairs. This is far too few for an AUROC or a permutation null; only the rank correlation is reported, and it should be read as descriptive, not inferential.
+
+| predictor | Spearman vs realised rescue |
+|---|---|
+| weight_cosine | -0.400 |
+| d_raw | -0.400 |
+| qmd_perm | -0.400 |
+| coord_share_perm | 0.000 |
+| qmd_orth | -0.400 |
+| coord_share_orth | 0.000 |
+| bnd_raw | 0.200 |
+| bnd_perm | 0.200 |
+| bnd_orth | 0.200 |
+| coord_share_bnd_perm | 0.000 |
+| coord_share_bnd_orth | 0.000 |
+| cka_mean | -0.400 |
+| cka_last | 0.400 |
+| qmd_act_perm | 0.400 |
+| qmd_act_procrustes | 0.400 |
+| qmd_act_ot | 0.400 |
+| vocab_overlap | -0.200 |
+| weight_cosine_body | -0.200 |
+
+## Control · is the obstruction the INIT seed or the DATA order?
+
+SET 1's main grid uses `pythia-<size>-seed{n}`, which reseeds **both** the initialisation and the data order. `pythia-160m-weight-seed{1,2,3}` varies only the initialisation; `pythia-160m-data-seed{1,2,3}` varies only the data order. Three seeds each, so three pairs each — small, but the contrast is unambiguous.
+
+| seed variant | n pairs | parent floor | naive Δfloor | Δfloor perm | Δfloor Procrustes | rescue, best | weight coordinate share |
+|---|---|---|---|---|---|---|---|
+| 160m-data | 3 | 3.27 | 3.13 | 3.00 | 3.00 | 3.9% | 0.0139 |
+| 160m-weight | 3 | 3.25 | 3.10 | 2.79 | 2.79 | 10.0% | 0.0123 |
+| 160m (init+data, main grid) | 16 | 3.25 | 8.56 | 6.67 | 6.28 | 28.6% | 0.0936 |
+
+Reading: models that differ **only in data order** start far closer together — the naive merge's
+Δfloor is a small fraction of the reseeded-init case — and alignment does **nothing** for them,
+because there is no coordinate mismatch to remove. Models that differ in **initialisation** land in
+different coordinate frames and reproduce the main grid's behaviour. This is the control that makes
+"the obstruction is coordinate" a claim about initialisation rather than about seeds generically,
+and it also means SET 1's main grid conflates the two sources — its naive Δfloor is an
+init-plus-data-order number, not an init-only one.
+
+
+### What P0-2 comes to
+
+**Within a single substrate, nothing predicts the realised rescue.** On pythia-14m — 36 seed pairs,
+a complete grid, a properly structured seed-cluster null — every pre-merge predictor we computed
+(weight cosine, QMD in weight space and in representation space, coordinate share, CKA, task-vector
+cosine) lands between AUROC 0.30 and 0.68 held out by seed, and **not one survives BH correction**.
+The multivariate ridge over all of them does no better. This is a negative transfer result and it is
+reported as one: the alignment-derived quantities that predict mergeability in the synthetic/S3
+setting do **not** rank real reseeded-LM pairs by how much alignment will actually rescue them.
+
+**Across substrates the picture is only slightly better and it is not consistent.** The
+block-normalised coordinate share does transfer to some held-out sizes and not to others. Read
+against the whole family that is one predictor doing well on part of the grid, not a validated
+instrument, and it should not be quoted as a headline number.
+
+Two honest caveats in the other direction. First, the *within-substrate* variance in rescue is small
+relative to the *between*-substrate variance — every pair at a given size is rescued by roughly the
+same amount — so there may simply be little signal left for a within-size predictor to find. Second,
+the seed-cluster null is conservative by construction. Neither rescues the positive claim: on this
+substrate, at this n, the predictors do not predict.
+
 
 ## Coverage — what ran and what did not
 
 | cell | n | status | what was measured |
 |---|---|---|---|
 | SET 1 · pythia-14m | 36/36 seed pairs | complete | M0 naive · M1 permutation · M1 Procrustes · M2 task-arithmetic · M3 TIES; barrier for M0 and M1-perm |
-| SET 1 · pythia-70m | 13/36 seed pairs | partial | M0 naive · M1 permutation · M1 Procrustes · M2 task-arithmetic · M3 TIES; barrier for M0 and M1-perm |
-| SET 1 · pythia-160m | 4/36 seed pairs | partial | M0 naive · M1 permutation · M1 Procrustes · M2 task-arithmetic · M3 TIES; barrier for M0 and M1-perm |
-| SET 4 · goldfish eng×X | 1/4 language pairs (nld_Latn) | partial | M0 naive · M1a vocab-transport · M1b/c vocab+unit-aligned (perm/Procrustes) · M1d/e forced-residual · M1f unit-aligned only |
-| BLiMP / MultiBLiMP accuracy | 0 | **NOT RUN** | No benchmark harness was close to wired inside this window. Deliberately not built from scratch. The Δfloor results below therefore say nothing about accuracy. |
+| SET 1 · pythia-70m | 34/36 seed pairs | partial | M0 naive · M1 permutation · M1 Procrustes · M2 task-arithmetic · M3 TIES; barrier for M0 and M1-perm |
+| SET 1 · pythia-160m | 16/36 seed pairs | partial | M0 naive · M1 permutation · M1 Procrustes · M2 task-arithmetic · M3 TIES; barrier for M0 and M1-perm |
+| SET 4 · goldfish eng×X | 4/4 language pairs (nld_Latn, spa_Latn, ell_Grek, pol_Latn) | complete | M0 naive · M1a vocab-transport · M1b/c vocab+unit-aligned (perm/Procrustes) · M1d/e forced-residual · M1f unit-aligned only |
+| BLiMP accuracy · SET 1 (English) | pythia-14m: 36/36 pairs, pythia-70m: 9/36 pairs | RAN | 67 paradigms from `nyu-mll/blimp`, minimal-pair sentence-logprob scoring, on the SAME merges as the Δfloor tables |
+| MultiBLiMP / any accuracy benchmark · SET 4 (Goldfish) | 0 | **NOT RUN** | No multilingual benchmark harness was close to wired inside this window; deliberately not built from scratch. SET 4's numbers are likelihood only and say nothing about accuracy. |
 | B-GPT joint bilingual reference | 0 | **NOT RUN** | Out of window; the merged models are not compared against a jointly-trained bilingual ceiling. |
 | Goldfish 160m/other tiers, other language pairs | 0 | NOT RUN | Only the 1000mb tier and the four audit languages. |