{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003555759,0.00009342995,0.0001423589,0.0005091177,0.0001075813,0.00009734075,0.0001006718,0.00008988506,0.0002797035],"category_scores_gemma":[0.00005931092,0.00008741776,0.00002539826,0.0009040436,0.00001977803,0.0004143975,0.00008296379,0.0001290405,0.0005214574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002514646,"about_ca_system_score_gemma":0.00003932231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1109242,"about_ca_topic_score_gemma":0.3682945,"domain_scores_codex":[0.9991654,0.000005362973,0.0002538274,0.0001647294,0.0001053916,0.0003053199],"domain_scores_gemma":[0.9997345,0.00002064146,0.00007932423,0.0001234924,0.00003477848,0.000007295712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007895727,0.00001177873,0.6270676,0.0001305356,0.000005998741,0.00002248992,0.0002020547,0.000009155687,0.0000202019,0.3338573,0.0363108,0.002354187],"study_design_scores_gemma":[0.001394279,0.00002064869,0.26366,0.0002739393,0.00001247164,0.000006665462,0.00990981,0.01593958,0.0000226503,0.03240503,0.675828,0.0005269945],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9282579,0.000009769355,0.0004578802,0.007692882,0.0005192559,0.0003091628,5.880863e-7,0.0008133003,0.06193926],"genre_scores_gemma":[0.9963226,0.000002689247,0.00001808382,0.001016199,0.00015491,0.00001248653,0.00003448614,0.00001440774,0.002424139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6395172,"threshold_uncertainty_score":0.8949962,"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."}}