{"id":"W3085544470","doi":"10.2196/23604","title":"Medical Students' Corner: Lessons From COVID-19 in Equity, Adaptability, and Community for the Future of Medical Education","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Innovations in Medical Education","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Adaptability; Coronavirus disease 2019 (COVID-19); Equity (law); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medical education; Political science; Psychology; Medicine; Economics; Infectious disease (medical specialty); Virology; Management; Disease","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","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0069715,0.0002568164,0.0005623219,0.0001836681,0.0003248494,0.00005063398,0.001477513,0.0008524678,0.003689424],"category_scores_gemma":[0.05793385,0.0001944986,0.0001051821,0.0009884434,0.0009355997,0.0001323373,0.0006619234,0.002458505,0.00001019222],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004574597,"about_ca_system_score_gemma":0.02799704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002099523,"about_ca_topic_score_gemma":0.001084528,"domain_scores_codex":[0.9926075,0.0006712425,0.001161266,0.0004781533,0.004732776,0.0003491111],"domain_scores_gemma":[0.99472,0.001996133,0.0003597426,0.0008138789,0.0005125355,0.001597745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003627289,0.008175598,0.07212348,0.001224272,0.00008869698,0.000002897753,0.01341306,4.854041e-7,0.00001838281,0.01175853,0.2020333,0.6907986],"study_design_scores_gemma":[0.009283538,0.0009747274,0.4530915,0.002136144,0.0003793333,0.0001474386,0.09410492,0.01196149,0.00004380637,0.01245895,0.4147809,0.0006372123],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4757643,0.001288494,0.001621749,0.5183002,0.001452023,0.001363792,0.00001401831,0.00004879535,0.0001466116],"genre_scores_gemma":[0.8956348,0.0008124412,0.0007843265,0.09821808,0.002781936,0.001017044,0.0006723407,0.00003255907,0.00004644074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6901614,"threshold_uncertainty_score":0.9998429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06447142819866512,"score_gpt":0.4896667206752779,"score_spread":0.4251952924766128,"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."}}