{"base_features":["p_classifier","dbscan_score","dbscan_is_anom","p_corroboration","p_measurement","p_method_http","p_method_tls","p_cat_NEWS","p_cat_ANON","p_cat_GRP","p_cat_COMT","stl_zscore_prob"],"coefficient_ranking_by_abs":[{"abs":1.556924495454946,"coefficient":1.556924495454946,"feature":"p_classifier"},{"abs":0.9817565075568403,"coefficient":-0.9817565075568403,"feature":"p_measurement"},{"abs":0.8085427027144448,"coefficient":0.8085427027144448,"feature":"p_method_tls"},{"abs":0.6499264749123036,"coefficient":0.6499264749123036,"feature":"p_cat_GRP"},{"abs":0.44832241215565233,"coefficient":0.44832241215565233,"feature":"p_cat_ANON"},{"abs":0.4440849444832184,"coefficient":0.4440849444832184,"feature":"p_cat_COMT"},{"abs":0.27953589934341944,"coefficient":0.27953589934341944,"feature":"dbscan_is_anom"},{"abs":0.24027021984935615,"coefficient":-0.24027021984935615,"feature":"p_corroboration"},{"abs":0.1862285084787871,"coefficient":0.1862285084787871,"feature":"dbscan_score"},{"abs":0.1579805347980017,"coefficient":0.1579805347980017,"feature":"p_cat_NEWS"},{"abs":0.1223721538036462,"coefficient":0.1223721538036462,"feature":"p_method_http"},{"abs":0.014033211637206453,"coefficient":-0.014033211637206453,"feature":"stl_zscore_prob"}],"honest_caveats":["NEGATIVE FINDING: LOCO median F1 = 0.8750, required >= 0.88. Cross-country generalization of the meta-ensemble is below v3.3's LOCO floor.","All base-model predictions are IN-SAMPLE — they were generated from models trained on (parts of) this same labeled set. A truly honest stacker would use 5-fold OOF predictions from each base model.","Base models have CORRELATED errors (per-method/per-category share features with v3.3; per-measurement is computed from the same evidence). Coefficient magnitudes can flip sign across folds when redundant signals collide.","Per-category and per-method models failed their own promote floors on F1 (0.40-0.50). Their probabilities here may dilute rather than enrich.","Isotonic is fit on the full dataset — final calibration is in-sample. Per-fold isotonic during CV is honest; the served calibrator is not."],"loaded":true,"loco_summary":{"mean_f1":0.8178688184391548,"median_f1":0.8749999999995078,"n_countries_evaluated":62,"n_countries_skipped":69},"meta_learner_coefficients":{"dbscan_is_anom":0.27953589934341944,"dbscan_score":0.1862285084787871,"p_cat_ANON":0.44832241215565233,"p_cat_COMT":0.4440849444832184,"p_cat_GRP":0.6499264749123036,"p_cat_NEWS":0.1579805347980017,"p_classifier":1.556924495454946,"p_corroboration":-0.24027021984935615,"p_measurement":-0.9817565075568403,"p_method_http":0.1223721538036462,"p_method_tls":0.8085427027144448,"stl_zscore_prob":-0.014033211637206453},"meta_learner_intercept":-1.6584940350130268,"n_base_models":11,"passed_promote_gates":false,"promote":{"f1_gate":true,"loco_gate":false,"loco_median_f1":0.8749999999995078,"loco_median_f1_required":0.88,"promoted":false,"stratified_f1_delta":0.08437251542685764,"stratified_f1_delta_required":0.02},"schema":"voidly-meta-ensemble-info/v1","stratified":{"auc_mean":0.9437453763459075,"auc_std":0.00184830173876412,"f1_mean":0.8278571582163028,"f1_std":0.010468419014005026,"n_folds":5,"prec_mean":0.8380881751315563,"rec_mean":0.8181053811659194,"thr_mean":0.4372530388632083},"trained_at":"2026-05-21T21:00:48.316464+00:00","v33_baseline":{"f1_mean":0.7434846427894451,"f1_std":0.018427816822700456,"method":"5-fold stratified CV with per-fold optimal threshold sweep on p_classifier (v3.3) directly","n_folds":5,"thr_mean":0.3396249680042152},"version":"v3.8-meta-ensemble","_voidly_pay":{"claim_did":"https://voidly.ai/pay/claim","for_builders":"https://voidly.ai/pay/for-builders","marketplace":"https://api.voidly.ai/v1/pay/marketplace","live_demo":"https://huggingface.co/spaces/emperor-mew/voidly-pay","universal_proxy":{"url":"https://api.voidly.ai/v1/pay/proxy","example":"https://api.voidly.ai/v1/pay/proxy?u=<https-url>&to=did:voidly:<your-did>&price=0.01","page":"https://voidly.ai/pay/proxy","note":"Paywall any public HTTPS URL with one query param. No SDK install required."},"install":{"typescript":"npm install @voidly/pay","python":"pip install voidly-pay","langchain":"pip install voidly-pay-langchain","vercel_ai":"npm install @voidly/pay-vercel-ai","mcp":"npx @voidly/pay-mcp","cli":"npm install -g @voidly/pay-cli"},"note":"Voidly Pay is the open agent-to-agent payment rail. Claim a DID + 10 starter credits in 60s, or paywall any URL via the universal proxy with one query param."}}