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aientity · corroborated across sources

graphrag

for ml engineers, ai researchers

Steady

20

signal score

as of 1d ago

1

live items

Cooling

7-day est. ~6

devto

Why this scored 20

every term, weighted
Velocity+0.0 / 40 max

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

Acceleration+11.0 / 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+9.4 / 10 max

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

Saturation penalty0.5 / 30 max

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

Composite20.0

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

~6

range 018

14-day

~0

range 04

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. 118

    The Same GraphRAG Comparison Wins and Loses. It Depends Which Instrument Judged It.

    Benchmark outcomes for GraphRAG differ by evaluation metric, so choose metrics wisely. — for ml engineers, ai researchers

    devtoaiSteady2d ago