{"id":"W4413844967","doi":"10.24926/jrmc.v8i2.6760","title":"Getting the job done: educational robustness of a multi-campus Longitudinal Integrated Clerkship during the COVID-19 pandemic","year":2025,"lang":"en","type":"article","venue":"Journal of Regional Medical Campuses","topic":"Online and Blended Learning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"NOSM University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Robustness (evolution); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computer science; Medical education; Medicine; Virology; Internal medicine; Biology; Infectious disease (medical specialty)","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":[0.004400957,0.0002166089,0.000218833,0.0004203962,0.003138996,0.002785394,0.00109763,0.0005201646,0.002664474],"category_scores_gemma":[0.01199544,0.0001936935,0.0002711487,0.0003525633,0.001393522,0.0009459804,0.004531416,0.0009882372,0.0002749248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005145656,"about_ca_system_score_gemma":0.01005886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03314011,"about_ca_topic_score_gemma":0.1129186,"domain_scores_codex":[0.9974338,0.001153937,0.00006116607,0.0001713014,0.0003611402,0.0008186927],"domain_scores_gemma":[0.9931912,0.0009162409,0.0006472692,0.0003734042,0.0007755148,0.004096413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009041021,0.01056983,0.643672,0.0002131613,0.0001162176,0.001578972,0.144314,0.001392224,0.003387435,0.0009608275,0.007084106,0.185807],"study_design_scores_gemma":[0.00005650539,0.003775586,0.7423989,0.0001186989,0.00004197494,0.0002780144,0.2410068,0.001574602,0.0009065373,0.0003787369,0.009394274,0.00006932984],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99792,0.00002152443,0.0001253779,0.0004439033,0.0000174253,0.0000513594,0.00002503465,0.000008928304,0.001386639],"genre_scores_gemma":[0.9990612,0.00002493633,0.0002104814,0.0001047053,0.00000568295,0.00002899215,0.00003215971,0.000002618734,0.0005292681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03314011,"threshold_uncertainty_score":0.06589442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06551753552397474,"score_gpt":0.3924114505440416,"score_spread":0.3268939150200668,"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."}}