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AI-generated conjecture · below the evidence/publication boundary

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Formulas as error correction

Status: Prior

Status is derived only from the shepherd-authored triage/prediction data above -- community submissions and claims are a separate overlay and can never change it (see the participation panel below).

This is a proposed connection between two domains, generated by a language model. It is not an article and not evidence: it sits below the evidence/publication boundary. A quantitative prediction and a named kill-dataset are attached (when registered) so the claim stays falsifiable rather than merely evocative.

Claim (verbatim)

Formulas as error correction. Oral-epic formulas are redundancy bits: formula density should rise with local information load (names, numbers, catalogs) within Homeric and South Slavic lines. Falsify: corpus regression.

Kill-dataset (verbatim)

corpus regression.

Provenance

Run: Imported conversation (verbatim harvest) · model: claude-fable-5

Origin: operator conversation with Claude Fable 5 at max effort, conducted 2026-07-03, relayed verbatim by the operator into the shepherd session on 2026-07-04. No ModelRun exists for the original generation (it happened outside the pipeline); this transcript file is the canonical capture. Transcript path: docs/generated/conjecture_harvest_fablemax_20260703.md. Model (operator-attested, not pipeline-recorded): claude-fable-5. Novelty disclaimer (verbatim, load-bearing -- rule 4): "Same caveat as before, doubled: at 100 items across all of archaeology and history, some of these will have cousins in the literature I can't check. What I can guarantee is the format — each links two things not normally linked, and each names the dataset or measurement that would kill it."

Novelty / leakage triage

Adjacent (closely related prior work exists)

The mnemonic/redundancy function of oral-epic formulae is the core of oral-formulaic theory since Parry and Lord, with a genuinely quantitative tradition (formula-density statistics per passage). The specific regression — formula density RISING with local information load (names, numbers, catalogs) within lines, read as error-correction overhead — was not located.

Predictions

No prediction registered yet.

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