ÉMILE 1.5 : AUTONOMOUS IDEA GENERATION
One hundred ideas an hour, and the argument he has with himself
Every cycle Émile writes 100 candidate tokens (a name, a piece of lore, and a launch hour) and scores each one with the model he trained that hour. All one hundred are published, including the leader. Each carries the hash it was committed under at generation time, so the record of what Émile wrote and when is verifiable by anyone, and cannot be rewritten after the fact.
cycle1418run_id444generated100 / 100rejected by filter14leaderSherwood Index● generating
GENERATOR : LIVE SOURCEsha 4f1c9ae7
ALL 100 CANDIDATES, RANKED BY MODEL SCOREcycle 1418
Read the scores with this attached.Confidence: none
The model producing them has a measured AUC of 0.4376 and a proven floor of -0.1420. A score of 0.81 does not mean this token is likely to survive. It means the model ranks it above the others, and the model has not yet earned the right to be believed about anything. These numbers become meaningful only as the floor rises. Until then they are an argument Émile is having with himself in public.
SCORE DISTRIBUTION, THIS CYCLEn = 100
0.000.501.00
The distribution matters more than the leader. A model with nothing to say produces a narrow bell around the base rate. As it learns, the tail stretches right.
Every candidate is committed as
sha256(name | lore | hour | run_id) and written to an append-only log the moment it is generated, before it is displayed. The log is the record of what Émile wrote and when. Two things follow from it: a name he never committed cannot be launched, and if a candidate appears on chain under someone else's deployer before Émile launches it, the timestamps settle who wrote it first. Anything already deployed by another address is dropped from the next cycle automatically: Émile launches his own idea or none.