{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03969784,0.0001982001,0.001227804,0.00005006592,0.0001479371,0.00003042654,0.0001148768,0.0003022257,0.00001845723],"category_scores_gemma":[0.03169439,0.0001550548,0.000315052,0.0003749358,0.0006018812,0.0001281059,0.00006209806,0.0005046676,0.00001653361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004374434,"about_ca_system_score_gemma":0.003449724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001774469,"about_ca_topic_score_gemma":0.0002767587,"domain_scores_codex":[0.9919572,0.002386853,0.003688794,0.0007266768,0.0008351994,0.0004052284],"domain_scores_gemma":[0.9939211,0.003275991,0.001436839,0.0004222303,0.000621011,0.0003228288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.6370236,0.001212071,0.07727432,0.006100497,0.0002764253,0.00000521996,0.0003000649,0.000005770913,0.00001001533,0.01419708,0.02656108,0.2370338],"study_design_scores_gemma":[0.4476449,0.006731763,0.5039411,0.003570892,0.0001204884,0.00001507656,0.0005789184,0.0002973815,0.000003494516,0.00931295,0.02741299,0.0003701177],"study_design_candidate":"randomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8071384,0.003936248,0.0001435743,0.1727287,0.005505304,0.01027829,0.00007010146,0.0000512114,0.0001481241],"genre_scores_gemma":[0.9528145,0.003184991,0.01688765,0.0171336,0.008308765,0.000426817,0.0006542993,0.00003081,0.0005585657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4266668,"threshold_uncertainty_score":0.9888331,"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."}}