{"id":"W4309265332","doi":"10.2196/40039","title":"Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Hospital for Sick Children","funders":"","keywords":"Implementation; Workload; Qualitative research; Machine learning; Health care; Medicine; Qualitative property; Computer science; Artificial intelligence; Medical education","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.1359923,0.0007298409,0.0008556413,0.004084963,0.003722225,0.005637654,0.002283734,0.001636464,0.005651365],"category_scores_gemma":[0.123562,0.001067228,0.001368248,0.005098255,0.003236466,0.005481123,0.004927198,0.002204192,0.0004358465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008134213,"about_ca_system_score_gemma":0.0127322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005325806,"about_ca_topic_score_gemma":0.008684717,"domain_scores_codex":[0.8469462,0.1338909,0.005430358,0.002889316,0.006958317,0.00388489],"domain_scores_gemma":[0.7870278,0.1728872,0.0183044,0.005296502,0.01338224,0.003101863],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007957583,0.002361393,0.1968738,0.005726504,0.0006132441,0.001155406,0.6696725,0.0006328119,0.0009118429,0.01447233,0.003190467,0.1035938],"study_design_scores_gemma":[0.0002833134,0.00290516,0.0553754,0.006312358,0.0003231239,0.0008989578,0.9031515,0.0031417,0.00142272,0.00572911,0.02031696,0.0001398148],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9528519,0.00470691,0.02435474,0.005975192,0.0001619527,0.005330842,0.0006782759,0.00003401093,0.005906207],"genre_scores_gemma":[0.9498547,0.003167612,0.02933438,0.005026476,0.0001313476,0.01098224,0.0002690578,0.00004266867,0.001191394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8640077,"threshold_uncertainty_score":0.7192045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1225206310448115,"score_gpt":0.5402283784443398,"score_spread":0.4177077473995283,"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."}}