Github Trends®
7872 findingsmedian surprise 0.00437window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #5612 · UNIT ID 1196855016
elizabetht/100-days-of-inference
100 days of LLM inference engineering — daily posts, experiments, and visualizations
[ JUPYTER NOTEBOOK ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0532
ENGAGEMENT0.51
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
4% 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
S10 · DEAD CODE, ZERO CONTRIBUTORS, YET STARS KEEP DRIPPING

Growth Telemetry

VELOCITY /D
15.33
ACCEL
+4.00
RETENTION
85.0%
PEAK 2026-09-07 · FORK-RETENTION 44.4% · 46 STARS / WINDOW

Author Audience

AUDIENCE
248
FOLLOWERS
120
OWNER ★
1,289

Engagement Signals

FORKS
123
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 46 / 46 (DIVERSITY 1.00)

Why This Is A Finding

elizabetht/100-days-of-inference собрал 46 звёзд за окно, тогда как у автора всего 120 подписчиков — эффективная аудитория ≈ 248. Это даёт surprise-индекс 0.0532 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 44.4% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 7872 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 29%
VELOCITY15.335.67+9.67ABOVE 81%
RETENTION85.0%0.0%+85.0 PPABOVE 96%
FORKS123365-242ABOVE 31%
SURPRISE0.050.00+0.05ABOVE 89%