Github Trends®
8833 findingsmedian surprise 0.00433window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #4219 · 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

SURPRISE0.00152
ENGAGEMENT0.87
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
12.67
ACCEL
-6.50
RETENTION
45.0%
PEAK 2026-09-10 · FORK-RETENTION 68.8% · 38 STARS / WINDOW

Author Audience

AUDIENCE
8,316
FOLLOWERS
1,254
OWNER ★
29,040

Engagement Signals

FORKS
6,295
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 38 / 38 (DIVERSITY 1.00)

Why This Is A Finding

mlflow/mlflow собрал 38 звёзд за окно, тогда как у автора всего 1,254 подписчиков — эффективная аудитория ≈ 8,316. Это даёт surprise-индекс 0.00152 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 68.8% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 8833 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00+0.00ABOVE 52%
VELOCITY12.675.67+7.00ABOVE 77%
RETENTION45.0%45.9%-0.9 PPABOVE 49%
FORKS6,295344+5,951ABOVE 94%
SURPRISE0.000.00-0.00ABOVE 32%