FINDING #7342 · UNIT ID 841342273
SkylarShiHub/pumBayes
An R package for Bayesian estimation of probit unfolding models for binary preference data. This R package is described in the paper 'pumBayes: Estimating Ideal Points from Voting Data in R Using Unfolding Models' (2026). Journal of Open Research Software.
SURPRISE SCORE
0.00
Score Breakdown
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
61% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S1a · OWNER ACCOUNT AND REPO CREATED SAME DAY
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
10.71
ACCEL
-0.68
RETENTION
0.0%
PEAK 2026-08-08 · FORK-RETENTION 0.0% · 75 STARS / WINDOW
Author Audience
AUDIENCE
23
FOLLOWERS
8
OWNER ★
145
Engagement Signals
FORKS
2
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 75 / 75 (DIVERSITY 1.00)
Why This Is A Finding
SkylarShiHub/pumBayes собрал 75 звёзд за окно, тогда как у автора всего 8 подписчиков — эффективная аудитория ≈ 23. Это даёт surprise-индекс 0.17 (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 24% OF 9721 FINDINGS
METRICS IN CONTEXT
MEDIAN ACROSS ALL 9721 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 24%
VELOCITY10.713.43+7.29ABOVE 80%
RETENTION0.0%32.1%-32.1 PPABOVE 0%
FORKS2130-128ABOVE 3%
SURPRISE0.170.01+0.17ABOVE 98%