{"id":"W3092651983","doi":"10.1177/0846537120967720","title":"Imaging Database Preparation for Machine Learning","year":2020,"lang":"en","type":"article","venue":"Canadian Association of Radiologists Journal","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; McMaster University; Hamilton Health Sciences; Juravinski Hospital","funders":"","keywords":"Medicine; Medical physics; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.001106418,0.00009752248,0.0002794545,0.0001354036,0.0001975467,0.00004048911,0.00009770016,0.00006572952,0.00008634145],"category_scores_gemma":[0.008223436,0.00009118854,0.0001243309,0.0001280064,0.0000362488,0.0001128909,0.000009030305,0.0005815849,0.000005240909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005623288,"about_ca_system_score_gemma":0.000561857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008980077,"about_ca_topic_score_gemma":0.0004412388,"domain_scores_codex":[0.9988863,0.0001109975,0.0003535393,0.0001537603,0.0002014483,0.0002939913],"domain_scores_gemma":[0.9984637,0.0001796103,0.0004228806,0.00006826382,0.0002423339,0.0006232168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002475663,0.00002851221,0.8525344,0.0001258707,0.0002646648,0.0001165909,0.00101303,0.001982185,0.006251683,0.0006333201,0.1158294,0.02097277],"study_design_scores_gemma":[0.005044054,0.0006413739,0.03423576,0.000133334,0.0002796957,0.0006131906,0.0002318596,0.4612561,0.0003633592,0.000239361,0.4966509,0.0003109282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3529864,0.004365415,0.2527014,0.375504,0.002060337,0.001829329,0.0003744113,0.0002525978,0.009926097],"genre_scores_gemma":[0.9869052,0.0001734109,0.007532272,0.003989918,0.0007167165,0.000004636202,0.0001976843,0.00002067355,0.0004594589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8182987,"threshold_uncertainty_score":0.9844815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708624331981382,"score_gpt":0.2945726153428971,"score_spread":0.2774863720230832,"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."}}