How a score is worked out › ledger-strict@0.1.0

ledger-strict@0.1.0

The cautious counterpart. It refuses to score the claim types where reasonable models differ most — causal and interpretive — rather than produce a number it would have to hedge. Where the two models disagree about a claim, that disagreement is itself reported, on the weaknesses page.

Version 0.1.0. The algorithm as first specified: relevance, observation, interpretation, authenticity and extraction, strongest-only within each independence group, log-odds combination.

Released at entry seq 2 · config sha256:0e03475107bd65f59cd695c1179a883ea67b4e0fa028493582dfb108e51c4a45 · code sha256:b1357011dab1871f639065bec5574c8a4e4a3481ccbb754f52541f7a1a4d304c

A released model never changes. Those two hashes are recorded in every score it produced, so any number it has ever given can be reproduced exactly, by this node or by anyone else.

Where it differs from ledger-default@0.1.0

Released alongside it, from the same code, with different settings.

Setting	ledger-default@0.1.0	ledger-strict@0.1.0
types it marks as model-dependent	causal, interpretive	none
observation weight: expert analysis	0.3	0.0
prior: causal	0.35	not declared
prior: interpretive	0.50	not declared
claim types it scores	observational, quantitative, historical, textual, comparative, definitional, attributed belief, causal, interpretive	observational, quantitative, historical, textual, comparative, definitional, attributed belief

What it scores, and what it declines to

Scored: observational, quantitative, historical, textual, comparative, definitional, and attributed belief.

Every other claim type gets not applicable from this model and no probability at all — a refusal to score, not a score of nought.

Every number it declares

What each of these means, and why it is there, is on how a score is worked out.

Prior by claim type

Setting	Value
textual	0.50
historical	0.50
comparative	0.50
definitional	0.50
quantitative	0.50
observational	0.50
attributed belief	0.50

Relevance

Setting	Value
weak	0.2
direct	2.0
strong	1.2
moderate	0.6
context only	0.0

Observation

Setting	Value
other	0.1
hearsay	0.1
eyewitness	0.4
calculation	0.7
direct text	0.9
measurement	1.0
model output	0.0
archaeological	0.9
dataset result	0.9
expert analysis	0.0

Authenticity

Setting	Value
doubtful	0.3
verified	1.0
unverified	1.0

Extraction

Setting	Value
verified	1.0
unverified	1.0

State thresholds

Setting	Value
supported	0.80
leans supported	0.60
unresolved above	0.40
leans contradicted above	0.20

The rest

Setting	Value
interpretive step penalty	0.15
independence	strongest only per group and direction
rounding	mode half_even, weights 6, coverage 2, probability 4, boundary guard 1e-6
review checks	primary source reviewed, opposing search done, independence reviewed, qualifiers reviewed
primary source types	primary text, dataset, measurement, legal document