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ideadet-logreg-1m-items
Idea-level AI-text detector: a logistic-regression head over frozen
text-embedding-3-large vectors (3072 dimensions). It answers whose ideas a
document contains, not who typed the sentences.
- Training corpus: 1m, 12,749,656 training rows
- Reads at inference: individual outline items, each embedded separately and pooled to the document by logit mean
- Hyper-parameters: C=1.0, max_iter=3000
Contents
lr_items_v1m.npz holds coef ((1, 3072)), intercept, and the fitting metadata.
AI is the positive class, so the reported score is predict_proba(x)[:, 0] = P(human), and
the detector fires when that falls below a calibrated threshold. Thresholds are quantiles
over held-out human documents and are not included here: a cut from one model or input
form is meaningless against another's scores.
Provenance
This model was refit from the stored embeddings, because the original runs saved only their predictions. The refit was checked against those published test predictions and reproduces them to max |difference| = 4.98e-07, so it is the same model that produced the reported numbers rather than an approximation.
Fuller documentation and evaluation results to follow.