AI-generated conjecture · below the evidence/publication boundary
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Computus as checksum
Status: No prior located
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)
Computus as checksum. Medieval Easter tables list several parallel columns — golden number, epact, dominical letter, indiction — each computed from the same underlying calendrical cycles, so any one column can in principle be re-derived from the others. That mutual derivability is exactly the structure of a redundant error-correcting code: a slip in one column becomes detectable because it no longer agrees with its neighbours. The claim is that medieval users did not merely copy these columns mechanically but actually exercised this redundancy to catch and repair mistakes. If so, the redundancy should leave a statistical fingerprint: in collated computus manuscripts, columns that can be cross-checked against other columns should carry markedly fewer surviving errors, and the corrections scribes did make should cluster precisely where the cross-check would have flagged them.
Prediction clause (verbatim)
In collated computus manuscripts, scribal error rates in columns checkable against other columns run ≥2x lower than in uncheckable columns of the same tables, and in-manuscript corrections concentrate in the checkable columns.
Kill-dataset (verbatim)
Kill: collations of the Bede-tradition Easter tables; equal error rates across column types kills it.
Nobody has run this test.
The kill-data is named above. If you can run it — or you know the paper that already settles it —
claim the kill or submit the prior.
Kills and priors are credited here, by name, as they come in.
In the atlas
This conjecture is bridged, as an L1 lead, onto these Inferpedia subject pages.
Provenance
Run: Fresh agent generation
· model: claude-fable-5
Authored by the shepherd session (Claude Fable 5) as the recorded instrument, drafted 2026-07-04 in the session scratchpad (fresh_conjectures_draft_20260704.md) after Phase A was launched and BEFORE any triage literature search for this pilot; imported immediately after Phase A deployment and before the B2 triage pass began, so the fresh-lane ModelRun timestamp precedes all triage ModelRuns. Novelty unverified: the author cannot rule out prior formulations in the literature; these enter the same triage lane as the imported harvest.
Novelty / leakage triage
no prior formulation located (search dated 2026-07-04)
Computus scholarship is deep and scribal errors in Easter tables are noted anecdotally (e.g., century-insertion errors), but no study was located comparing error rates between mutually-checkable and free columns of the same tables, or examining in-manuscript corrections by column class. No prior formulation located (search dated 2026-07-04).
Predictions
Open
registered 2026-07-04
OPEN prediction: in collated computus manuscripts, scribal error rates in columns checkable against other columns of the same table run at least 2x lower than in uncheckable columns, and in-manuscript corrections concentrate in checkable columns.
Resolution criteria: Resolvable by collating Easter tables across a manuscript family (e.g., the Bede tradition) and classifying each column as mutually-derivable or free. SUPPORTED if the checkable-column error rate is <= half the free-column rate with a significant difference (p < 0.05, clustered by manuscript), AND corrections are overrepresented in checkable columns. KILLED if error rates are statistically indistinguishable across column classes.
Known priors disclosure: No collated computus data in-house. The registrant knows computus errors are attested anecdotally but has seen no per-column error statistics.
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