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663 findingsmedian surprise 0.00061window 30 days
UNIT / TREND-MONITOR · REV 2.6
[ 30 days window ]
SOURCE: gharchive
FINDING #614 · UNIT ID 1384094559
Contrastive-LM/CLM
Contrastive Language Models (CLMs) are a new class of System One model trained with a contrastive learning objective that connects states and actions.
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SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.00274
ENGAGEMENT0.31
FRESHNESS1.12
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
2% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S2 · NO EXTERNAL ISSUE/PR AUTHORS DESPITE 100+ STARS
S7 · THIS REPO IS ~ALL OF THE OWNER'S STARS
S9 · CREATED JUST BEFORE WINDOW, STARS INVISIBLE IN ARCHIVE

Growth Telemetry

VELOCITY /D
2.00
ACCEL
-0.01
RETENTION
16.7%
PEAK 2026-09-24 · FORK-RETENTION 0.0% · 60 STARS / WINDOW

Author Audience

AUDIENCE
689
FOLLOWERS
44
OWNER ★
3,007

Engagement Signals

FORKS
262
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 60 / 60 (DIVERSITY 1.00)

Why This Is A Finding

Contrastive-LM/CLM собрал 60 звёзд за окно, тогда как у автора всего 44 подписчиков — эффективная аудитория ≈ 689. Это даёт surprise-индекс 0.00274 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 663 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 7%
VELOCITY2.002.77-0.77ABOVE 28%
RETENTION16.7%11.1%+5.5 PPABOVE 73%
FORKS2621,805-1,543ABOVE 14%
SURPRISE0.000.00+0.00ABOVE 78%