{"id":"W2945328036","doi":"10.1016/j.conctc.2019.100380","title":"Trends in clinical trial investigator workforce and turnover: An analysis of the U.S. FDA 1572 BMIS database","year":2019,"lang":"en","type":"article","venue":"Contemporary Clinical Trials Communications","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Janssen Pharmaceuticals; AstraZeneca; U.S. Food and Drug Administration; Eli Lilly and Company; Bristol-Myers Squibb; Sanofi; Merck; Daiichi-Sankyo; Amgen","keywords":"Medicine; Confidence interval; Clinical trial; Workforce; Food and drug administration; Clinical research; Demography; Family medicine; Gerontology; Database; Internal medicine; Medical emergency; Political science; Computer science","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"],"consensus_categories":[],"category_scores_codex":[0.0131104,0.0003271798,0.0006739727,0.006531222,0.00061014,0.002079652,0.001355257,0.0006415136,0.001452114],"category_scores_gemma":[0.03844227,0.0004305553,0.0006294906,0.01123415,0.0003612629,0.001140335,0.001563662,0.0009228684,0.0008744489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001964638,"about_ca_system_score_gemma":0.003152657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02700264,"about_ca_topic_score_gemma":0.02743251,"domain_scores_codex":[0.9873001,0.003077563,0.003094521,0.002201879,0.003446566,0.0008793085],"domain_scores_gemma":[0.918059,0.01676795,0.04502551,0.003425181,0.01298296,0.003739378],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002310936,0.0000520076,0.9859395,0.00007536058,0.00009490126,0.00004122513,0.0001997486,0.0002159223,0.0001128893,0.0001107216,0.005818934,0.007107596],"study_design_scores_gemma":[0.00004151372,0.0000813684,0.990734,0.0001056801,0.00005777819,0.0002069995,0.0006644432,0.001891788,0.0002110769,0.00007153711,0.00591733,0.00001656794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9392068,0.002076133,0.0007513043,0.001380791,0.00004454069,0.0001098125,0.05335753,0.000102405,0.002970669],"genre_scores_gemma":[0.9312029,0.001391285,0.002198681,0.001006686,0.00009660701,0.0003738895,0.06255632,0.00005837519,0.001115251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9868896,"threshold_uncertainty_score":0.06933522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8880603768098574,"score_gpt":0.686476495085422,"score_spread":0.2015838817244354,"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."}}