{"id":"W4205916580","doi":"10.1109/bigdata52589.2021.9671738","title":"Predicting family physicians based on their practice using machine learning","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Big Data (Big Data)","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"NOSM University; Lakehead University","funders":"","keywords":"Machine learning; Rurality; Artificial intelligence; Computer science; Health care; Binary classification; Field (mathematics); Class (philosophy); Medicine; Rural area; Support vector machine; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001282851,0.0003700957,0.0004273979,0.003070548,0.0003064522,0.0006948589,0.00039678,0.0007542698,0.001236224],"category_scores_gemma":[0.00918502,0.0001704495,0.0004812856,0.002033933,0.0001995209,0.0007011142,0.0002988167,0.0004842212,0.0004990358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006950145,"about_ca_system_score_gemma":0.0008340497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01552714,"about_ca_topic_score_gemma":0.01653318,"domain_scores_codex":[0.9990729,0.0003131691,0.0001016212,0.0001665503,0.0002360649,0.0001097589],"domain_scores_gemma":[0.9940724,0.003917972,0.001003754,0.0001385262,0.0006340768,0.0002332943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008840846,0.0002162083,0.9418603,0.00003623701,0.00005890986,0.0001357231,0.0001096118,0.02365882,0.0002081533,0.00018772,0.001044528,0.03239542],"study_design_scores_gemma":[0.00002811372,0.0002460155,0.4215892,0.00005445819,0.00005402698,0.0003234638,0.00048235,0.5741881,0.0007274528,0.001177285,0.001098742,0.00003076069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802316,0.0006313676,0.01454895,0.0007866228,0.00003166083,0.00007535316,0.001371343,0.0001690344,0.00215418],"genre_scores_gemma":[0.9917682,0.0002282218,0.00650646,0.00004964308,0.00002818028,0.00002968499,0.001017696,0.000003852267,0.0003680503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01552714,"threshold_uncertainty_score":0.03087348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6762616049797713,"score_gpt":0.5199363785259139,"score_spread":0.1563252264538574,"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."}}