{"id":"W3149290894","doi":"10.47912/jscdm.31","title":"Electronic Data Capture-Study Conduct, Maintenance and Closeout","year":2021,"lang":"en","type":"article","venue":"Journal of the Society for Clinical Data Management","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Inflamax Research (Canada)","funders":"","keywords":"Data collection; Electronic data capture; Automatic identification and data capture; Data management; Computer science; Best practice; Database; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.02547046,0.0001493894,0.0006070229,0.00001699461,0.0001711467,0.0000900945,0.002866377,0.0002043012,0.0000364455],"category_scores_gemma":[0.02237435,0.00009033013,0.000704032,0.0002222259,0.0004123687,0.0002569994,0.007074355,0.003013291,0.000004354551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009440278,"about_ca_system_score_gemma":0.000690814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007176146,"about_ca_topic_score_gemma":0.00008177598,"domain_scores_codex":[0.9960217,0.0002573028,0.001428901,0.0006988304,0.001166253,0.0004269534],"domain_scores_gemma":[0.986839,0.006566122,0.0006646481,0.004932564,0.0007414359,0.0002562233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008312245,0.003639639,0.02099026,0.001061656,0.01004182,0.0002323702,0.0002303233,0.000002741593,0.00002545379,0.01208935,0.9342497,0.01660548],"study_design_scores_gemma":[0.01504431,0.001916855,0.0363937,0.0008896582,0.005482776,0.0002233197,0.009621533,0.001935764,0.00001064514,0.04671626,0.8814461,0.0003190359],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.263777,0.02934284,0.01620526,0.6653323,0.008621366,0.009307649,0.002322964,0.00008690364,0.005003707],"genre_scores_gemma":[0.6820882,0.1604733,0.07487818,0.0368128,0.003427184,0.00002551489,0.000554741,0.0001475956,0.04159252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6285195,"threshold_uncertainty_score":0.9992868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7200875333063134,"score_gpt":0.6312750633354082,"score_spread":0.0888124699709052,"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."}}