Three of four corners of the evidence matrix existed. The missing one was
forward-only *and* key-restricted — which is exactly what per-competitor
prequential scoring needs, the intersection of the two workloads
`log_evidence_for` and `filtered_log_evidence` are each documented for.
`filtered_log_evidence_for` fills it. It is not
`log_evidence_internal(true, targets)`: that path selects `skill.forward`
as the prior, which stops being a filtering quantity once `iteration`
has run a backward sweep. It goes through `filtered_pass` like its
unrestricted sibling, with the restriction applied to which events are
*scored*, never to which are *run* — so it is a held-out score under the
real history, not a score under a counterfactual one where nobody else
played.
Key resolution for both `*_for` accessors now shares `resolve_targets`,
so they cannot drift apart on how an unknown key is reported.
`current_skills` is the plural of `current_skill`. Building a
leaderboard previously meant materialising every competitor's full
smoothed curve via `learning_curves` and reading the last point of each.
Tests carry controls in both directions: naming every competitor must
recover the unrestricted value (catching a filter that drops too much),
and the restricted forward-only value must differ from the restricted
smoothed one (catching an alias).
Refs #70.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
