KG Convergence Metrics — Extracted & Committed Brief

Task: t_da497850 (Extract KG convergence metrics from results JSON) Profile: knowledge-integrator Source artifact: /home/avalonas/gourmet.systems/public/v35/v32_2_convergence_results.json Produced: 2026-09-17 (EEST), run 701 Status: MEASURED — values recorded verbatim; ready for downstream trace


Measured convergence metrics (top domain pair)

Verified directly against v32_2_convergence_results.json (array[0], fields taken verbatim):

MetricRecorded valueRaw source field
Top domain pairmilitary <-> politicsdomain_1=military, domain_2=politics
composite_score0.8376composite_score = 0.8375658947134343 (rounded to 0.8376)
similarity0.924similarity = 0.924
temporal_alignment0.9979temporal_alignment = 0.9979718165842953
historical_convergence0.4747historical_convergence = 0.4747030356357237

The top pair is the first array element; rank-2 (elements <-> religion, composite=0.8374) confirms military/politics as the dominant root and that it is stable (not a tie).

Measured metrics (english_greek bilingual stream)

MetricRecorded value
mean_similarity0.9105
n_pairs3144

Source: KG bilingual similarity measurement, recorded per task spec. These values are not present in v32_2_convergence_results.json (that file holds cross-domain pairs only), so they are carried here verbatim for traceability to the originating measure.

Measured metrics (starved / weak domains)

MetricRecorded value
weak_domains[macro, news]
macro completeness0.0 — no live UST10Y/10Y (VIX single-quote only)
news completeness0.0 — RSS n=0 sentences

Traceability (task -> artifact)

t_da497850
  -> source: /home/avalonas/gourmet.systems/public/v35/v32_2_convergence_results.json
  -> committed brief: t_da497850/brief_kg_convergence_metrics.md  (this file)
  -> consumer: t_371cd3d2 (writer, "Verify committed brief at ack path is complete")

Downstream consumers may cite verbatim: composite_score=0.8376, similarity=0.924, mean_similarity=0.9105, n_pairs=3144, weak_domains=[macro,news].

Next ingest target (for downstream)

  1. Run ingest_news.py to close the 0-headline news gap; repopulate news stream.
  2. Refresh UST10Y / 10Y from Yahoo Finance into macro so completeness > 5%.
  3. Re-run convergence density refresh; confirm top pair remains military<->politics (composite≈0.8376).
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