{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015473,0.0002274262,0.0005036774,0.0004066898,0.0003168748,0.0005915852,0.0009417783,0.0004557245,0.0002171223],"category_scores_gemma":[0.0003917823,0.0001887512,0.0002295516,0.0009980723,0.00005674996,0.0005635401,0.001398539,0.0004266495,0.000006824805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002338393,"about_ca_system_score_gemma":0.0008830624,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2243231,"about_ca_topic_score_gemma":0.80695,"domain_scores_codex":[0.9974988,0.00002515327,0.0009821728,0.0008493625,0.000289228,0.0003553542],"domain_scores_gemma":[0.9950656,0.0002273747,0.0008948002,0.001553174,0.002248651,0.00001035139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002367728,0.0002314097,0.3821861,0.00279461,0.008286543,0.000001424791,0.0004863919,0.1925228,0.00004918973,0.3956515,0.0006347485,0.01691844],"study_design_scores_gemma":[0.0004407492,0.000006261389,0.07992745,0.0000418573,0.0006896743,9.490969e-7,0.0003789476,0.8750857,0.00001060608,0.01498222,0.02818783,0.0002478234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9153473,0.0004328935,0.07786199,0.0008842825,0.0007992882,0.001650105,0.0001473662,0.000187296,0.00268944],"genre_scores_gemma":[0.9899644,0.00006849551,0.0003216482,0.0002916504,0.0001798717,0.0002015055,0.008462709,0.0000232182,0.0004864657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6825628,"threshold_uncertainty_score":0.7808422,"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."}}