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Kaggle is offering cash prizes for a benchmarking challenge, encouraging participation in ML model evaluation.

Cooling
Signal score
19
as of 1d ago
Trajectory
⏳ Too early
needs a few more snapshots

Why this scored 19

every term, weighted
Velocity+8.9 / 40

Engagement gained per hour since the last capture, against the fastest item on its own source

Acceleration+0.4 / 25

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

Cross-source spread+0.0 / 25

How many independent communities are talking about the same entity

Recency+9.9 / 10

Decays to zero over 14 days

Saturation penalty−0.1 / 30

Subtracted once something is big and old — we rank what's next, not what's peaked

Composite19.1

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic'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

Signal history

7-day window (free)
1975

Entities

kaggle
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[![Signalcrest signal](https://www.signalcrest.app/api/badge/dev%3A4727332)](https://www.signalcrest.app/topic/dev%3A4727332)

Drop this in a README or blog post — it updates automatically as the score moves.