{"id":"W4391219375","doi":"10.21203/rs.3.rs-3788203/v1","title":"Harmonizing quality improvement metrics across global trial networks to advance paediatric clinical trials delivery","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta","funders":"European Commission; Novartis Pharmaceuticals Corporation; Chiesi Farmaceutici; European Federation of Pharmaceutical Industries and Associations; Eli Lilly and Company; U.S. Department of Health and Human Services","keywords":"Clinical trial; Quality (philosophy); Quality management; Medicine; Computer science; Operations management; Engineering; Internal medicine","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":["metaresearch"],"category_scores_codex":[0.3246646,0.001296357,0.001535735,0.01165254,0.002577945,0.01665086,0.004341457,0.002034733,0.004170468],"category_scores_gemma":[0.5203667,0.000782022,0.001609357,0.01539378,0.003091962,0.021945,0.01405477,0.004637055,0.001475351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02200532,"about_ca_system_score_gemma":0.04791963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01070323,"about_ca_topic_score_gemma":0.01080628,"domain_scores_codex":[0.6914857,0.2114103,0.04271867,0.01042343,0.03752697,0.006434971],"domain_scores_gemma":[0.3851132,0.2453088,0.08939885,0.05581278,0.2013832,0.02298318],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004457198,0.0004312889,0.1358213,0.006086748,0.0008050806,0.0001915688,0.01579663,0.01442667,0.001844918,0.07572991,0.07516414,0.6732561],"study_design_scores_gemma":[0.0004038434,0.002395994,0.1944049,0.02168542,0.0007473704,0.0005007764,0.02737962,0.05406104,0.009125594,0.1902195,0.4982463,0.0008297952],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1128835,0.01461639,0.5844087,0.1749308,0.003259586,0.01206703,0.00799993,0.005539286,0.08429487],"genre_scores_gemma":[0.4760077,0.005104213,0.4884732,0.008586917,0.0007236594,0.009757893,0.006777246,0.001320235,0.003248919],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6753354,"threshold_uncertainty_score":0.8328089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8173218366692324,"score_gpt":0.7305881743254286,"score_spread":0.08673366234380386,"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."}}