{"id":"W4361766319","doi":"10.17496/kmer.2018.20.1.6","title":"Development and Operation of Longitudinal Integrated Clerkship","year":2018,"lang":"en","type":"article","venue":"Korean Medical Education Review","topic":"Innovations in Medical Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical school; Variety (cybernetics); Medical education; Longitudinal study; Block (permutation group theory); Medicine; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01768155,0.0002955336,0.000382635,0.002089696,0.0006613731,0.001712123,0.002201646,0.0007015193,0.003370898],"category_scores_gemma":[0.01299746,0.0002808938,0.0005279535,0.001376301,0.0004798654,0.00184921,0.003350734,0.001118996,0.0009772857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003125841,"about_ca_system_score_gemma":0.01788105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003467303,"about_ca_topic_score_gemma":0.007263403,"domain_scores_codex":[0.9950375,0.002286477,0.0005152067,0.000517269,0.0009529733,0.000690649],"domain_scores_gemma":[0.9885862,0.001865286,0.001489671,0.0006479461,0.004429367,0.002981432],"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":[0.0001379017,0.001257717,0.01247431,0.001886766,0.00003894841,0.0001444802,0.00111012,0.0008342214,0.001162502,0.009319312,0.006197717,0.9654362],"study_design_scores_gemma":[0.001072727,0.01163353,0.2248456,0.009410702,0.0003260098,0.002813227,0.00785613,0.008687765,0.01018564,0.006624638,0.7163086,0.0002355008],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5559728,0.1846443,0.1017008,0.0290333,0.003014056,0.01205719,0.0009181571,0.001880381,0.1107791],"genre_scores_gemma":[0.7572032,0.0554975,0.1600866,0.004446352,0.000661963,0.002430176,0.001019698,0.00009209058,0.01856247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01768155,"threshold_uncertainty_score":0.09351009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03414857590989395,"score_gpt":0.3872042311341654,"score_spread":0.3530556552242714,"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."}}