{"id":"W4387983449","doi":"10.2196/49825","title":"Continuing Medical Education in the Post COVID-19 Pandemic Era","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Innovations in Medical Education","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Continuing medical education; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Medical education; Process (computing); Continuing education; Public relations; Business; Political science; Medicine; Computer science; Infectious disease (medical specialty); Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004559263,0.0002307929,0.0003258704,0.0007871377,0.0001798191,0.00005034425,0.0005617572,0.0005706278,0.004286335],"category_scores_gemma":[0.04645265,0.000172852,0.00009451687,0.002869728,0.0003519322,0.0001761961,0.00006900163,0.00150949,0.000592733],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006157982,"about_ca_system_score_gemma":0.0263584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003604461,"about_ca_topic_score_gemma":0.0001533446,"domain_scores_codex":[0.9951763,0.0003360033,0.0008959515,0.0004996306,0.002589308,0.0005027928],"domain_scores_gemma":[0.9975362,0.0004939601,0.0002069309,0.0006730942,0.0004291203,0.000660635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005289087,0.001573547,0.07213122,0.0002671782,0.00001315773,0.00001790296,0.007526281,5.232408e-7,0.00004023537,0.004154209,0.3737683,0.5404546],"study_design_scores_gemma":[0.002118512,0.0001698098,0.452789,0.00129224,0.00005963886,0.001038249,0.02241254,0.001773893,0.00000624844,0.001974846,0.5160127,0.0003522973],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7755848,0.0002186725,0.0001039247,0.2168874,0.002481483,0.00114643,0.000001460827,0.0002501157,0.003325682],"genre_scores_gemma":[0.8322852,0.0002648315,0.0003185851,0.1595576,0.002392918,0.001424395,0.00133203,0.00003988877,0.002384557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5401023,"threshold_uncertainty_score":0.9966239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02025388793414004,"score_gpt":0.4250593635326465,"score_spread":0.4048054755985064,"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."}}