{"id":"W4242687025","doi":"10.2196/preprints.32101","title":"The Ontario Electronic Consultation (eConsult) Service: Cross-sectional Analysis of Utilization Data for 2 Models (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Specialty; Directory; Medicine; Service (business); Primary care; Family medicine; Service delivery framework; Computer science; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006183784,0.0005674725,0.0005516854,0.002168681,0.000767027,0.001007918,0.001590547,0.0005792666,0.009716979],"category_scores_gemma":[0.02343775,0.0005761898,0.001677911,0.006660433,0.0004887122,0.0008427708,0.0012167,0.0007131667,0.001356235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01459011,"about_ca_system_score_gemma":0.01392132,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8785571,"about_ca_topic_score_gemma":0.8583351,"domain_scores_codex":[0.9951468,0.001802972,0.0004375679,0.0004886251,0.001399325,0.0007247404],"domain_scores_gemma":[0.9781447,0.008038129,0.00578559,0.002000864,0.00460522,0.001425526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004598545,0.0001962871,0.9800547,0.0001111524,0.0003060672,0.0000472391,0.0004590839,0.001177439,0.00007297949,0.0002658993,0.01264593,0.004203356],"study_design_scores_gemma":[0.00008614584,0.0002475698,0.985131,0.00006363722,0.0001226276,0.00006939303,0.00112191,0.009278998,0.00008844173,0.00007488864,0.003684619,0.00003081829],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9209785,0.0003584949,0.001848901,0.0005225017,0.0000344739,0.0007097682,0.07185129,0.0001339802,0.003562089],"genre_scores_gemma":[0.9403931,0.000277949,0.002312343,0.0001746438,0.00003449991,0.001041624,0.05216689,0.00006680479,0.003532111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1214429,"threshold_uncertainty_score":0.2443162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1407670380852942,"score_gpt":0.3508364948725773,"score_spread":0.2100694567872831,"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."}}