Github Trends®
5944 findingsmedian surprise 0.0104window 180 days
UNIT / TREND-MONITOR · REV 2.6
[ 180 days window ]
SOURCE: gharchive
FINDING #5362 · UNIT ID 1034938477
OpenDCAI/DataFlex
Data-centric LLM training with dynamic sample selection, domain mixture optimization, and example reweighting inside the LLaMA-Factory training loop.
[ PYTHON ][ ORG ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.00156
ENGAGEMENT0.20
FRESHNESS1.39
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
93% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S2 · NO EXTERNAL ISSUE/PR AUTHORS DESPITE 100+ STARS
S5 · PREDATES WINDOW, YET HALF+ OF ALL ITS STARS LANDED IN IT

Growth Telemetry

VELOCITY /D
7.72
ACCEL
+0.12
RETENTION
27.2%
PEAK 2026-04-21 · FORK-RETENTION 0.0% · 1,389 STARS / WINDOW

Author Audience

AUDIENCE
4,910
FOLLOWERS
1,139
OWNER ★
13,160

Engagement Signals

FORKS
198
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 1,389 / 1,389 (DIVERSITY 1.00)

Why This Is A Finding

OpenDCAI/DataFlex собрал 1,389 звёзд за окно, тогда как у автора всего 1,139 подписчиков — эффективная аудитория ≈ 4,910. Это даёт surprise-индекс 0.00156 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 5944 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 10%
VELOCITY7.723.29+4.42ABOVE 77%
RETENTION27.2%11.3%+15.9 PPABOVE 83%
FORKS19899+99ABOVE 69%
SURPRISE0.000.01-0.01ABOVE 20%