{"id":"W2620582323","doi":"10.1017/cjn.2017.191","title":"P.107 Standardizing resident operative-case logging: the first step of a prospective national study of resident operative volume","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Digital Imaging in Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; Sherbrooke O.E.M (Canada); Toronto Public Health; Alberta Hospital Edmonton; Systems, Applications & Products in Data Processing (Canada); Vancouver Biotech (Canada); University of Winnipeg","funders":"","keywords":"Neurosurgery; Medicine; Medical physics; Medical education; Surgery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.007439201,0.0003180917,0.0008039945,0.0007492555,0.004328086,0.0008399549,0.002119166,0.00009792008,0.0001085583],"category_scores_gemma":[0.01061687,0.0001768281,0.0002056921,0.0006414902,0.01222474,0.001375682,0.0001849801,0.00121791,9.844625e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003871293,"about_ca_system_score_gemma":0.004879391,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006112634,"about_ca_topic_score_gemma":0.1012117,"domain_scores_codex":[0.9948922,0.0006836574,0.001254907,0.0005237638,0.00182719,0.0008182301],"domain_scores_gemma":[0.9941593,0.0006360646,0.001680343,0.0003236893,0.002189558,0.001010983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002642009,0.0001055278,0.9711738,0.00001442754,0.00006510189,0.02046322,0.004091941,0.001735809,0.00003706269,0.0004243147,0.001222481,0.0004021402],"study_design_scores_gemma":[0.0018581,0.1333612,0.7617306,0.0002963854,0.0001693368,0.08536661,0.01034348,0.002587637,0.0003220701,0.002639666,0.001020108,0.0003048071],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854791,0.0005187925,0.00002800979,0.008436559,0.0005250814,0.000562984,0.00001878032,0.000007660783,0.004423],"genre_scores_gemma":[0.997889,0.0000690754,0.0006078766,0.00110609,0.0002312979,0.000006004861,1.259773e-7,0.00001159531,0.00007892089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2094432,"threshold_uncertainty_score":0.9977171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05674182487777644,"score_gpt":0.3501043905131253,"score_spread":0.2933625656353488,"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."}}