AI-generated conjecture · below the evidence/publication boundary
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Vedic vs vellum
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).
Claim (verbatim)
Vedic vs vellum. Vedic oral transmission's error rate per syllable-century is orders of magnitude below manuscript copying of comparable Sanskrit texts — quantify both for the first time. Falsify: Rigveda variant counts vs Mahābhārata manuscript variance.
Kill-dataset (verbatim)
Rigveda variant counts vs Mahābhārata manuscript variance.
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 qualitative comparison is published — Staal and others describe Vedic oral transmission as MORE precise than early manuscript transmission, attributing it to layered recitation redundancy — and the item itself only claims the quantification as new ('quantify both for the first time'). The computed per-syllable-century rate comparison (Rigveda variants vs Mahabharata critical-edition variance across ~1,259 collated manuscripts) was not located.
- Oral-transmission summary citing Staal 2008 — Qualitative oral-beats-manuscript fidelity claim
- Mahabharata critical edition overview — Enabling collation dataset
Predictions
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