{"id":"W4385398744","doi":"10.2196/50109","title":"Authors’ Reply to: 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":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"United States Medical Licensing Examination; Selection (genetic algorithm); Medical education; Process (computing); Medical school; Psychology; Computer science; Medicine; Artificial intelligence; Programming language","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":[0.009525513,0.0009993827,0.001317357,0.001338994,0.005328502,0.003935073,0.003939351,0.07109672,0.02072504],"category_scores_gemma":[0.08467278,0.001193066,0.002323692,0.001228979,0.003883936,0.00424422,0.003266167,0.04296808,0.01481915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006048447,"about_ca_system_score_gemma":0.01385997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02815542,"about_ca_topic_score_gemma":0.03285833,"domain_scores_codex":[0.9920776,0.001418266,0.001588734,0.0008764004,0.002489484,0.001549421],"domain_scores_gemma":[0.9533065,0.02170046,0.00287594,0.0009639013,0.01639511,0.004757996],"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":[0.00002058136,0.00001004777,0.0003551991,0.00003623658,0.00000581004,0.0001510456,0.000120644,0.000020262,0.00004650038,0.000499559,0.9972966,0.001437439],"study_design_scores_gemma":[0.0001291886,0.00005867991,0.003636003,0.0006035315,0.00005010918,0.0007585573,0.001307987,0.000235882,0.0004929344,0.00277664,0.9897814,0.0001691435],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00022798,0.0002488446,0.00009661642,0.9761335,0.02193284,0.00001728483,0.0001520668,0.00007818038,0.001112732],"genre_scores_gemma":[0.0009717158,0.0001444595,0.000112584,0.9871222,0.009262583,0.00003795886,0.00003106882,0.00002446567,0.002293007],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9904745,"threshold_uncertainty_score":0.06933218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0533446893062084,"score_gpt":0.3766636862175132,"score_spread":0.3233189969113048,"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."}}