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Signalcrest
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devtoolsentity · corroborated across sources

jupyternotebook

for data scientists, notebook users

Steady

19

signal score

1

live items

Cooling

7-day est. ~0

stackoverflow

Why this scored 19

every term, weighted
Velocity+0.0 / 40 max

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

Acceleration+11.4 / 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

Composite19.2

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, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Outlook

low confidence · estimate, not a guarantee

7-day

~0

range 00

14-day

~0

range 00

30-day

~0

range 00

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. 135

    How to extract valid Python code from .ipynb cells

    Extracting clean Python from .ipynb cells enables reliable automation and testing. — for data scientists, notebook users

    stackoverflowdevtoolsSteady🔗 3 · python2d ago