{"id":"W4283804153","doi":"10.1093/pch/pxac044","title":"Care maps: De-medicalizing children with medical complexity","year":2022,"lang":"en","type":"article","venue":"Paediatrics & Child Health","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; SickKids Foundation","funders":"","keywords":"Promotion (chess); Health care; Medical diagnosis; Nursing; Resource (disambiguation); Psychology; Medicine; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.004087522,0.0006696357,0.0003527484,0.003945441,0.004552111,0.004025366,0.001769717,0.001582851,0.01732166],"category_scores_gemma":[0.0344238,0.0004200531,0.0007855491,0.002247483,0.002120764,0.007077471,0.01017632,0.00241858,0.002761411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002680101,"about_ca_system_score_gemma":0.007973019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01116593,"about_ca_topic_score_gemma":0.02867021,"domain_scores_codex":[0.9962119,0.002060498,0.0002796403,0.0002707855,0.0008640471,0.0003131524],"domain_scores_gemma":[0.9890064,0.00457338,0.001478928,0.001079542,0.00216699,0.001694802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00011374,0.0003069297,0.0432367,0.001225343,0.00004483614,0.003004604,0.08503454,0.0006796757,0.0009152886,0.01988538,0.2906338,0.5549191],"study_design_scores_gemma":[0.00005084421,0.0002290169,0.03571941,0.002851238,0.0001127903,0.006364121,0.1556945,0.002411515,0.002488774,0.03173209,0.7621609,0.0001848642],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3685539,0.008776638,0.1016748,0.134852,0.005041698,0.002379437,0.005705359,0.005190325,0.3678259],"genre_scores_gemma":[0.6629184,0.0134602,0.2752666,0.007156542,0.0008728722,0.001808516,0.00303742,0.0009740752,0.03450524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01732166,"threshold_uncertainty_score":0.0579468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03742107246755966,"score_gpt":0.3661537373660186,"score_spread":0.328732664898459,"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."}}