Signalcrest
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dataentity · corroborated across sources

scikitimage

for data scientists

Steady

12

signal score

1

live items

Accelerating

7-day est. ~17

stackoverflow

Why this scored 12

every term, weighted
Velocity+4.4 / 40 max

Its fastest-moving item, measured against the pace of its own source

Acceleration+0.0 / 25 max

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25 max

How many independent communities its own items come from

Recency+8.5 / 10 max

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty0.7 / 30 max

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite12.3

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement. Full methodology

Outlook

low confidence · estimate, not a guarantee

7-day

~17

range 1321

14-day

~19

range 1424

30-day

~20

range 1326

Signal history

7-day window (free)

— — projected trajectory (estimate, not a guarantee)

The evidence

The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.

  1. 117

    Normalized Mutual Information (skimage) near-minimum (~1.03) for registered RGB-thermal images — expected or an issue?

    Image registration issue — for data scientists

    stackoverflowdataSteady🔗 3 · python2d ago