{"id":"W3167654141","doi":"10.2196/25621","title":"Analysis of Population Differences in Digital Conversations About Cancer Clinical Trials: Advanced Data Mining and Extraction Study","year":2021,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Stand Up To Cancer","keywords":"Clinical trial; Ethnic group; Population; Medicine; Data extraction; Psychology; MEDLINE; Pathology; Sociology; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005152367,0.0003914165,0.0005397183,0.004039912,0.0008065508,0.001499933,0.0004852895,0.0006994362,0.001652426],"category_scores_gemma":[0.02622152,0.0002396304,0.0009041844,0.003671312,0.0004278745,0.001492235,0.00160859,0.000813033,0.0007357576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008010307,"about_ca_system_score_gemma":0.001039938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00295891,"about_ca_topic_score_gemma":0.002959165,"domain_scores_codex":[0.994732,0.002519498,0.0008033293,0.0009020084,0.0007190724,0.0003239571],"domain_scores_gemma":[0.9726715,0.02010823,0.002800923,0.001542592,0.002442381,0.0004343389],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001027201,0.0009179732,0.7151226,0.001658212,0.0004259911,0.001056125,0.03783096,0.001223498,0.01001923,0.002292868,0.009467218,0.2189581],"study_design_scores_gemma":[0.0001003599,0.0005359937,0.8551269,0.0004903881,0.0005470079,0.001461767,0.05806749,0.03899315,0.008060235,0.003509223,0.03295377,0.0001536807],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688283,0.0004477184,0.01647641,0.0004655955,0.00006015877,0.0007864354,0.009602414,0.0001782947,0.003154655],"genre_scores_gemma":[0.9620584,0.0003334293,0.02381758,0.0002056758,0.00007963574,0.001621592,0.01081106,0.00004131858,0.001031402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9948477,"threshold_uncertainty_score":0.02724862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7992562615352641,"score_gpt":0.7213653593883921,"score_spread":0.077890902146872,"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."}}