{"id":"W4317878670","doi":"10.1370/afm.21.s1.3539","title":"Understanding Ontario eConsult Utilization in Rural vs. Urban Settings","year":2023,"lang":"en","type":"article","venue":"","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Specialty; Context (archaeology); Telemedicine; Rural area; Medicine; Population; Descriptive statistics; Health care; Family medicine; Geography; Environmental health; Economic growth","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":[0.001021752,0.0001818844,0.0002397401,0.001725713,0.002092917,0.001593823,0.001113636,0.0004045264,0.005531924],"category_scores_gemma":[0.006294739,0.0002707537,0.0004152136,0.005439267,0.001137568,0.00109927,0.001520907,0.0004091111,0.000313909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02976103,"about_ca_system_score_gemma":0.03243041,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9857453,"about_ca_topic_score_gemma":0.9911419,"domain_scores_codex":[0.9983395,0.0001928099,0.00009921766,0.0002015042,0.0004358125,0.0007310206],"domain_scores_gemma":[0.9958775,0.000496446,0.001494465,0.000120865,0.001059321,0.0009514634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007361396,0.0000403237,0.959634,0.0003378587,0.00004960448,0.0002018153,0.0100445,0.0001967894,0.000186962,0.00144226,0.01262016,0.01517208],"study_design_scores_gemma":[0.000007311741,0.00002072289,0.9797289,0.0002177133,0.00001759853,0.00005470205,0.01189565,0.0002243838,0.00003548342,0.0001293318,0.007656762,0.00001143624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551461,0.002096756,0.0004573901,0.008911893,0.00004874511,0.0001643639,0.01465827,0.0000252507,0.01849123],"genre_scores_gemma":[0.9934755,0.00123516,0.0002976278,0.0006792714,0.00002456713,0.0001101461,0.002309448,0.00001094622,0.001857502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02976103,"threshold_uncertainty_score":0.2159324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1220303728909878,"score_gpt":0.2714153122385661,"score_spread":0.1493849393475783,"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."}}