{"id":"W2941884214","doi":"10.1136/bmjgh-2019-edc.19","title":"OC 8469 REVIEWING INVESTIGATIONAL PRODUCT’S QUALITY ASSURANCE DOCUMENTATION IN MAJOR CLINICAL TRIAL REGISTRIES FOR POST-MARKETING CLINICAL TRIAL STUDIES","year":2019,"lang":"en","type":"article","venue":"BMJ Global Health","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Documentation; Quality (philosophy); Clinical trial; Quality assurance; Product (mathematics); Medicine; Standardization; Business; Good manufacturing practice; Marketing; Political science; Computer science; Internal medicine; Service (business)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2819775,0.0008156305,0.002173943,0.02380582,0.002845144,0.00724223,0.003689626,0.003232984,0.0359191],"category_scores_gemma":[0.5322926,0.001324834,0.001385572,0.01704819,0.002777313,0.005001008,0.004805755,0.002732118,0.02400323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005332426,"about_ca_system_score_gemma":0.04497709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004744587,"about_ca_topic_score_gemma":0.008592279,"domain_scores_codex":[0.7327044,0.1023449,0.1192438,0.00577714,0.03725231,0.002677455],"domain_scores_gemma":[0.2007495,0.2397495,0.1199502,0.07945833,0.3479229,0.01216968],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0009789211,0.0002005894,0.01094179,0.01674955,0.0001947564,0.0008713711,0.004004784,0.0002063109,0.002321279,0.003152082,0.6271328,0.3332458],"study_design_scores_gemma":[0.0002848208,0.0002186493,0.01065771,0.01232446,0.0001864206,0.0004768904,0.0008600022,0.0005676494,0.001477518,0.001167428,0.9716822,0.00009630498],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05466649,0.09340817,0.1142664,0.1669396,0.04047959,0.08790533,0.05909976,0.01611638,0.3671182],"genre_scores_gemma":[0.2220609,0.07119504,0.3563185,0.06867877,0.02764148,0.07178304,0.05420352,0.008820723,0.1192981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7180225,"threshold_uncertainty_score":0.8854496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3597320122343899,"score_gpt":0.6192127663959429,"score_spread":0.259480754161553,"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."}}