Github Trends®
9558 findingsmedian surprise 0.00429window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #4642 · UNIT ID 136202695
mlflow/mlflow
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
[ PYTHON ][ ORG ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.00141
ENGAGEMENT0.84
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
0% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
11.67
ACCEL
+2.50
RETENTION
0.0%
PEAK 2026-08-28 · FORK-RETENTION 0.0% · 35 STARS / WINDOW

Author Audience

AUDIENCE
8,232
FOLLOWERS
1,236
OWNER ★
28,834

Engagement Signals

FORKS
6,231
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 35 / 35 (DIVERSITY 1.00)

Why This Is A Finding

mlflow/mlflow собрал 35 звёзд за окно, тогда как у автора всего 1,236 подписчиков — эффективная аудитория ≈ 8,232. Это даёт surprise-индекс 0.00141 (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 9558 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00+0.00ABOVE 51%
VELOCITY11.675.67+6.00ABOVE 75%
RETENTION0.0%42.9%-42.9 PPABOVE 0%
FORKS6,231333+5,898ABOVE 95%
SURPRISE0.000.00-0.00ABOVE 31%