FINDING #255 · UNIT ID 1142958185
jakerdliu/OpenTrit-CHN
• OpenTrit, an open-source cross-framework mixed ternary toolkit, supports one-click conversion of mixed ternary models between PyTorch and TensorFlow. It encapsulates heterogeneous computing power scheduling and quantization optimization, addressing the issues of "framework dependency and poor usability" present in existing ternary tools.
SURPRISE SCORE
0.00
Score Breakdown
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
57% OF STARS IN ARCHIVE
Growth Telemetry
VELOCITY /D
1.91
ACCEL
-0.02
RETENTION
6.9%
PEAK 2026-03-14 · FORK-RETENTION 0.0% · 343 STARS / WINDOW
Author Audience
AUDIENCE
82
FOLLOWERS
22
OWNER ★
598
Engagement Signals
FORKS
30
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 343 / 343 (DIVERSITY 1.00)
Why This Is A Finding
jakerdliu/OpenTrit-CHN собрал 343 звёзд за окно, тогда как у автора всего 22 подписчиков — эффективная аудитория ≈ 82. Это даёт surprise-индекс 0.0156 (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.
Related Findings
RANKS ABOVE 91% OF 2987 FINDINGS
METRICS IN CONTEXT
MEDIAN ACROSS ALL 2987 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.010.00+0.01ABOVE 91%
VELOCITY1.912.84-0.94ABOVE 22%
RETENTION6.9%6.8%+0.1 PPABOVE 51%
FORKS301,068-1,038ABOVE 1%
SURPRISE0.020.00+0.01ABOVE 100%