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DIVERGE-CCR1 Result: Candidate-Relative Encoding Is Not Semantic Grounding

- implementation commits: ec6d2f3, then pre-result audit-alias correction c2ee33f; - training job: 744334 on one Newton H100; - development evaluation: 744340; - read-only attribution: 744352; - training seed/updates: 2026080623, exactly 1,000; - trainable/total parameters: 546,4…

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DIVERGE-CCR1 Result: Candidate-Relative Encoding Is Not Semantic Grounding

Status: closed negative at the opened development gate. Sealed confirmation was never evaluated.

Frozen execution

  • implementation commits: ec6d2f3, then pre-result audit-alias correction c2ee33f;
  • training job: 744334 on one Newton H100;
  • development evaluation: 744340;
  • read-only attribution: 744352;
  • training seed/updates: 2026080623, exactly 1,000;
  • trainable/total parameters: 546,433 / 1,009,618;
  • charged source bytes: 21,349,174 in 56.415 training seconds;
  • checkpoint SHA-256: dd5287181308b3c8aae3a21cba8a12f873d5294f63158313a4bd6eececa3dc1d;
  • training-report SHA-256: 2695cd21a8af40cc914e721f7e23d08c13cb116a4dcd359ba9b96c1bf8f1997b.

All 50,000 evidence and 50,000 query training assignments fit exactly. WORLD and numeric-EVIDENCE owner hashes remained bit-identical.

The fresh 256-episode confirmation board was generated before training from commit ec6d2f3. It contains 3,072 evidence items, 768 balanced queries, and 1,048,576 represented worlds. Source, query, identity, and entity overlap with training and SRP1 are all zero. Board/report SHA-256 values are 29923706...1ebf7 and 77ce453b...042d. Because development failed, this board remained unopened.

Development result

CCR1 reaches:

MeasureResultRequired
Evidence assignment2,097 / 3,072>= 3,070
Query assignment695 / 768>= 765
Fully sealed episodes0 / 256>= 255

Query renderer exact counts are 55, 128, 128, 128, 128, 128 of 128. Development evaluation SHA-256 is c87a51ed08a103a73a63f6446554d9a6cea57dee3fe2fb975a785ab92cf85d5f. The evaluation wrapper exited nonzero, so dependency-held confirmation job 744343 became unsatisfiable and was canceled.

Read-only attribution

The one allowed attribution crosses every development item with every held renderer:

  • EVIDENCE renderer 0: 159/3,072; renderers 1 and 2: 3,072/3,072 each;
  • QUERY renderer 0: 351/768; renderers 1--5: 768/768 each;
  • marker swap changes query accuracy only from 695/768 to 683/768, so the SELF/OTHER marker identity is not the causal decision variable;
  • canonical entity renaming changes 122 of 3,840 assignments;
  • renderer-0 signed margins are negative on average (-16.581 evidence, -0.834 query), while every passing renderer has a large positive margin.

Diagnostic SHA-256 is 86eae09bde4123ef0edf4552753d5dc5dc5f97dfa170e61ffbbacf46336b7178.

An independent data audit exposes the identifiability failure. In both 50,000-row source sets, every renderer has exactly one role order: even renderers always label first mention TARGET and odd renderers always label it DISTRACTOR. A model can therefore fit every training label by recognizing renderer/order without learning the semantic relation.

Decision

Close CCR1 without width, marker, duration, seed, renderer, warm-start, loss, or optimizer variants. Independent candidate encoding does not force candidate-relative semantics and retains mention-length leakage. It does not qualify raw-language PL1.

The successor must remove the confound before fitting and change the representation boundary: collapse every full mention to one anonymous, length-free token; encode one sentence once; jointly match two explicit role slots to the two mention contexts; and train on paired role orders within each lexical family. That successor is DIVERGE-RRG1.