{"id":"W2962866587","doi":"10.2196/14310","title":"A Good Practice–Compliant Clinical Trial Imaging Management System for Multicenter Clinical Trials: Development and Validation Study","year":2019,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workflow; Clinical trial; Protocol (science); Harmonization; Audit; Process management; Good laboratory practice; Medicine; Medical physics; Computer science; Quality assurance; Database; Engineering; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.077392,0.0008226854,0.0006239705,0.002011196,0.0009471438,0.00276735,0.002939847,0.001476651,0.002294556],"category_scores_gemma":[0.08779449,0.0008535197,0.001078453,0.001321693,0.001513796,0.003192287,0.002344855,0.001563033,0.001340087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001914202,"about_ca_system_score_gemma":0.01416845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001536479,"about_ca_topic_score_gemma":0.001489384,"domain_scores_codex":[0.9667767,0.0190731,0.004525498,0.001900039,0.006813348,0.0009112785],"domain_scores_gemma":[0.9199279,0.02704214,0.008400468,0.0151165,0.02642131,0.003091657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00606897,0.007215865,0.07973202,0.007167391,0.0009726482,0.001702483,0.007189805,0.0299767,0.08205455,0.02372521,0.05309934,0.701095],"study_design_scores_gemma":[0.008071519,0.03022172,0.1359315,0.006015133,0.002296126,0.004381872,0.002500416,0.3000167,0.1343112,0.01078635,0.3648247,0.0006428407],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2509443,0.002396183,0.6506016,0.004347958,0.0005987706,0.05029693,0.001916404,0.02647199,0.01242596],"genre_scores_gemma":[0.2037517,0.000713692,0.7766551,0.001025228,0.0001057209,0.01159965,0.003846773,0.0006271697,0.001674962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.077392,"threshold_uncertainty_score":0.4092929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1068061179297186,"score_gpt":0.4905019789847784,"score_spread":0.3836958610550598,"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."}}