OONI test-type meta-classifier: per-country diagnostic ranking (which test type matters where)

Voidly Atlas runs eight OONI test types every six hours: web_connectivity, signal, whatsapp, telegram, facebook_messenger, tor, http_invalid_request_line, http_header_field_manipulation. Until today all eight were treated as equal contributors to country-day censorship labels. The OONI test-type meta-classifier asks: for each country, which test type is MOST diagnostic of actual censorship? Pipeline: bucket evidence at (country, day, test_type) by parsing test_name= out of OONI Explorer URLs in evidence.source_url, compute per-bucket anomaly rate from upstream_claim "N/M measurements anomalous" pattern (or fallback to fraction of non-ok signal_type), label country-days positive iff a confirmed censorship/mixed incident covers them +/- 1 day (343 incidents in scope), fit a per (country, test_type) logistic regression (class_weight=balanced, standardized input), require >=5 positive AND >=5 negative days, score AUC in-sample, rank. 30 countries cleared the 50-labeled-day floor; 13 show an AUC range > 0.10 between best and worst test type — both promote gates passed. Globally web_connectivity wins #1 most often (12 countries), then tor (5), http_invalid_request_line (4), the rest at 2 each. Spotlight: Iran top test = tor at AUC 0.838 (classic Tor-bridge interference), Russia top test = web_connectivity at AUC 0.977 (TSPU broad-protocol fingerprint), China not viable (only 4 incidents in the 2y window — too few positive days for AUC). Honest caveats: AUC is in-sample (no train/test split), test types have wildly different probe densities so AUC is not perfectly apples-to-apples, diagnostic != causal, the +/- 1 day label window can leak signal between adjacent days. Live at GET /v1/atlas/ooni-test-diagnostic + /info + /<cc>.