{"id":"W3158654196","doi":"10.3138/jvme-2020-0069","title":"The Use of Adaptive Learning Technology to Enhance Learning in Clinical Veterinary Dermatology","year":2021,"lang":"en","type":"article","venue":"Journal of Veterinary Medical Education","topic":"Problem and Project Based Learning","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Test (biology); Medical education; Veterinary medicine; Medical physics; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.001284123,0.0002693482,0.0002353054,0.0005359238,0.0001789628,0.0006496988,0.0004179253,0.0003048893,0.003409704],"category_scores_gemma":[0.005432778,0.00009869993,0.0002594131,0.0002877133,0.0002897865,0.0004857347,0.000664764,0.0004414164,0.0006049036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001637174,"about_ca_system_score_gemma":0.0004667099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001263038,"about_ca_topic_score_gemma":0.0002902004,"domain_scores_codex":[0.9989619,0.000527234,0.00004866768,0.00007451912,0.0002992491,0.00008831424],"domain_scores_gemma":[0.9967254,0.002401421,0.0002984943,0.000127596,0.000161186,0.0002858163],"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":[0.0008133561,0.007710437,0.02408863,0.000866027,0.00005557241,0.0004344047,0.001302303,0.001325353,0.03089808,0.0005604086,0.001610867,0.9303346],"study_design_scores_gemma":[0.001394648,0.1071494,0.7022805,0.002063698,0.0003756837,0.01037381,0.005043514,0.01261342,0.08388769,0.008393104,0.06616762,0.0002568719],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637775,0.001477196,0.02289956,0.0006893642,0.0000811007,0.000634418,0.0000442382,0.0002415578,0.01015505],"genre_scores_gemma":[0.953687,0.001644642,0.04194911,0.0002374391,0.00006570803,0.0003497002,0.00005476917,0.00001430665,0.001997296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003409704,"threshold_uncertainty_score":0.0114066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1266311647707559,"score_gpt":0.4801378047385565,"score_spread":0.3535066399678006,"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."}}