{"id":"W4240009393","doi":"10.3138/jvme.38.4.320","title":"The North American Veterinary Medical Education Consortium (NAVMEC) Looks to Veterinary Medical Education for the Future: “Roadmap for Veterinary Medical Education in the 21st Century: Responsive, Collaborative, Flexible”","year":2011,"lang":"en","type":"article","venue":"Journal of Veterinary Medical Education","topic":"Veterinary Practice and Education Studies","field":"Health Professions","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Veterinary education; Veterinary medicine; Medicine; Medical education; Political science; Curriculum","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01374272,0.0008710886,0.001174655,0.0009870527,0.003482816,0.0001777319,0.003518153,0.0007603307,0.001481266],"category_scores_gemma":[0.03672121,0.000560264,0.0004364119,0.002311944,0.001774862,0.001168889,0.0007211428,0.003134281,0.00008612543],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001259122,"about_ca_system_score_gemma":0.1285009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004537566,"about_ca_topic_score_gemma":0.0004064245,"domain_scores_codex":[0.9850453,0.004335572,0.003574664,0.001055796,0.004417572,0.001571118],"domain_scores_gemma":[0.981039,0.007504805,0.002936643,0.001674751,0.004216318,0.002628521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01567913,0.008552535,0.004264505,0.0008079234,0.0003605822,0.00007610852,0.02788024,7.432826e-7,0.0001481499,0.004034507,0.2755122,0.6626833],"study_design_scores_gemma":[0.001708834,0.008370595,0.06105047,0.001520506,0.0002201612,0.003209167,0.1392174,0.00006789117,0.000004907236,0.0003687421,0.783707,0.0005543635],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7864389,0.00823348,0.0002626597,0.165866,0.03224583,0.004635031,0.00003930551,0.00008149131,0.002197295],"genre_scores_gemma":[0.8924999,0.02108952,0.00338935,0.05780727,0.01529045,0.008365324,0.0002494867,0.0002031522,0.001105578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.662129,"threshold_uncertainty_score":0.9996849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2088272380663867,"score_gpt":0.5090747295442606,"score_spread":0.3002474914778739,"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."}}