{"id":"W4385398923","doi":"10.2196/47763","title":"Additional Considerations for US Residency Selection After Pass/Fail USMLE Step 1. Comment on “The US Residency Selection Process After the United States Medical Licensing Examination Step 1 Pass/Fail Change: Overview for Applicants and Educators”","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"United States Medical Licensing Examination; Selection (genetic algorithm); Medical education; Process (computing); Residency training; Medicine; Medical school; Psychology; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02633507,0.001004314,0.001023637,0.002002113,0.008895538,0.005047816,0.005848064,0.05554837,0.03289223],"category_scores_gemma":[0.1022809,0.001093989,0.003449038,0.001314241,0.004313668,0.005009412,0.005829608,0.02779873,0.01386731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008213243,"about_ca_system_score_gemma":0.03053665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06782712,"about_ca_topic_score_gemma":0.1525722,"domain_scores_codex":[0.9749535,0.004962171,0.003563544,0.001738167,0.008930648,0.005851999],"domain_scores_gemma":[0.8500125,0.06671729,0.008779788,0.003096718,0.05271107,0.01868268],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002933546,0.00005027489,0.001463711,0.00006191016,0.000006644313,0.0002979506,0.0004412245,0.00005524092,0.0002327853,0.001874955,0.9896256,0.005860455],"study_design_scores_gemma":[0.0001634214,0.0002541038,0.02019172,0.001202978,0.00006705565,0.0009982724,0.003547009,0.0004859501,0.00127565,0.003849083,0.9676812,0.0002836523],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001410924,0.0005049837,0.000731229,0.9767908,0.008576417,0.0001377595,0.0003192819,0.0004892071,0.01103945],"genre_scores_gemma":[0.005412099,0.0002470703,0.001242284,0.9732485,0.004709831,0.0002259967,0.0001306187,0.0001100984,0.01467358],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9736649,"threshold_uncertainty_score":0.1392748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1055489268150388,"score_gpt":0.4424474308890369,"score_spread":0.3368985040739981,"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."}}