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Update README.md

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@@ -174,7 +174,7 @@ Item IDs (`jb16-...`) keep the set's working name from when it was built.
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  ## Scoring
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- `score.py` computes Capability, the mean of Intelligence and Calibration, as JevBench v1.6 defines them, with one
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  change for yes/no questions.
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  - Intelligence: accuracy corrected for chance, per question type and difficulty tier (tier weights: easy 0.1,
@@ -184,12 +184,6 @@ change for yes/no questions.
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  - Also reported, not part of Capability: for the 129 calibration items, the mean distance between the predicted and
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  the true probabilities (`target_probs`), measured as total variation distance (0 = exact, 1 = completely wrong).
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- Note: JevBench v1.6 counts a yes/no answer with P(yes) between 0.2 and 0.8 as an abstention, which is scored as
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- wrong. OpenDecisions drops this rule. The exact definitions are in the docstring of `score.py`.
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-
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- We ran 17 public systems the way their authors serve them and scored them with JevBench v1.6's own rule. For the 14
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- with an official Capability of 55 or more, OpenDecisions ranks them close to the official JevBench v1.6.1 board
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- (Spearman correlation 0.90).
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  ## Leaderboard (October 15, 2026)
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@@ -245,10 +239,9 @@ and some public systems use temperatures we fitted.
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  ## Changes
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- - **1.0.1** (October 15, 2026): removed fields that were constant, duplicated or internal (`split`, `jb16`,
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- `panel_probs`, `provenance.label_basis`, `panel.flag`); added `trap_answer`; documented `target_probs`; `score.py`
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  also reports the distance to the true probabilities on the calibration items; quick start added; the split is
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- named `test` instead of `train`; leaderboard added. Items, labels and scores are unchanged.
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  ## Licence
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  ## Scoring
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+ `score.py` computes Capability, the mean of Intelligence and Calibration, with one
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  change for yes/no questions.
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  - Intelligence: accuracy corrected for chance, per question type and difficulty tier (tier weights: easy 0.1,
 
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  - Also reported, not part of Capability: for the 129 calibration items, the mean distance between the predicted and
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  the true probabilities (`target_probs`), measured as total variation distance (0 = exact, 1 = completely wrong).
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  ## Leaderboard (October 15, 2026)
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  ## Changes
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+ - **1.0.1** (October 15, 2026): removed stray fields; added `trap_answer`; documented `target_probs`; `score.py`
 
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  also reports the distance to the true probabilities on the calibration items; quick start added; the split is
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+ named `test` instead of `train`; leaderboard added. Items, labels, and scores are unchanged.
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  ## Licence
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