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kev — tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own

kev is a lightweight decision-model library built on Qwen3.5 for on-device training and inference.

Steady
Signal score
45
Sources
2
agreeing on kev
Trajectory
Accelerating
7-day est. ~41

Why this scored 45

every term, weighted
Velocity+16.1 / 40

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

Acceleration+14.4 / 25

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

Cross-source spread+12.5 / 25

How many independent communities are talking about the same entity

Recency+7.2 / 10

Decays to zero over 14 days

Saturation penalty5.6 / 30

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

Composite44.6

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

Outlook

low confidence · estimate, not a guarantee

7-day

~41

range 053

14-day

~45

range 160

30-day

~47

range 066

Signal history

7-day window (free)
1845

projected trajectory (estimate, not a guarantee)

Entities

kevqwen3.5
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Drop this in a README or blog post — it updates automatically as the score moves.