feat(models): make retrieval and fusion score semantics explicit (#90)

[Muhammad-AbdullahGhani]

Related issue

Closes #90

Summary

• Add explicit ranking and score semantics across models, CLI, evidence delivery, and MCP tools:
  • SearchHit: added channel_rank, score_kind='ordering_only', score_direction='higher_is_better', score_conversion='negated_distance', distance_metric='cosine', and distance_direction='lower_is_better'.
  • FusedMoment: added combined_rank, score_kind='ordering_only', score_direction='higher_is_better', scoring_method='reciprocal_rank_fusion', contributing_channels, and channels_run.
  • FusionProvenance: added score_kind='ordering_only', score_direction='higher_is_better', and scoring_method='reciprocal_rank_fusion'.
  • EvidenceBoardCandidate: added score_kind='ordering_only' and score_direction='higher_is_better' when candidate score is present.
• Backwards compatibility: all new fields include defaults and validators so existing callers and consumers remain fully compatible.
• CLI: updated emit_search table caption and headers (Score (RRF ↑), Contributing Channels) to clarify that scores are ordering-only values rather than calibrated probabilities.
• MCP: documented in search_moments and evidence_index that candidate scores and ranks are uncalibrated ordering values where higher is better.

Validation

• pytest tests/test_search.py tests/test_search_fusion.py tests/test_query_service.py tests/test_evidence_delivery.py -p no:asyncio (37 passed)
• pytest tests/test_cli.py -k search -p no:asyncio (2 passed)
• ruff check src/vidxp/application_models.py src/vidxp/capabilities/search.py src/vidxp/search_fusion.py src/vidxp/cli_support.py src/vidxp/evidence_delivery.py src/vidxp/mcp.py tests/test_search.py tests/test_search_fusion.py (All checks passed)
• ruff format --check src/vidxp/application_models.py src/vidxp/capabilities/search.py src/vidxp/search_fusion.py src/vidxp/cli_support.py src/vidxp/evidence_delivery.py src/vidxp/mcp.py tests/test_search.py tests/test_search_fusion.py (8 files already formatted)

[SaadBazaz]

Hey @Muhammad-AbdullahGhani,
Thanks for the Pull Request.
As a starter, we require all contributors to "star" and "fork" the repo, in order to determine if there really is a human behind the wheel or an autonomous agent.
Please star the repo for our review to proceed.
Thanks!

[Muhammad-AbdullahGhani]

Hi @SaadBazaz, I have starred and forked the repo..

[tulayha]

Thanks for working on this. We’re continuing with #144 for #90, so I’m closing this overlapping implementation.

This version hardcodes cosine even though indexes can use other distance metrics, and adds duplicate rank and channel fields that need to stay synchronized. #144 reads the configured metric and uses the existing fields, though it still needs changes from review.

If you’d like to contribute further to this issue, feel free to coordinate with @AhmedIrfan7 on #144. I’ve left specific feedback there that you could work through together.

Your bounded-moment fix in #141 is merged. Thanks for following through on that.