{"id":"W2963451163","doi":"10.1038/d41586-019-02241-z","title":"How a data detective exposed suspicious medical trials","year":2019,"lang":"en","type":"article","venue":"Nature","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"Medical practice; Medical research; Medical education; Medicine; History; Family medicine; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.1252382,0.001060705,0.001694944,0.006351341,0.002884825,0.01457665,0.003677861,0.01068642,0.01631217],"category_scores_gemma":[0.5148226,0.001721195,0.002421245,0.001739126,0.004347946,0.01404694,0.006412343,0.01159627,0.005167778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003422987,"about_ca_system_score_gemma":0.01117969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002200856,"about_ca_topic_score_gemma":0.002184993,"domain_scores_codex":[0.8774207,0.08110004,0.01247093,0.01020221,0.01676382,0.002042226],"domain_scores_gemma":[0.4118511,0.4670673,0.03631444,0.03885861,0.03280189,0.0131066],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003810355,0.0008021262,0.0824346,0.001932653,0.001350609,0.003799219,0.005274628,0.002165581,0.003830737,0.06975076,0.2443827,0.580466],"study_design_scores_gemma":[0.001291077,0.001944754,0.01874223,0.004352203,0.002188819,0.006857663,0.004533432,0.02943387,0.01865193,0.4123412,0.4990706,0.00059226],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04046695,0.006168938,0.1886309,0.6899211,0.0133766,0.001982214,0.001814235,0.00611342,0.05152567],"genre_scores_gemma":[0.4472559,0.002814229,0.3048823,0.1951607,0.01364837,0.001874084,0.0008906606,0.002174376,0.03129928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9893136,"threshold_uncertainty_score":0.6623308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05097257065999793,"score_gpt":0.3510392493535145,"score_spread":0.3000666786935166,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}