{"id":"W4322620256","doi":"10.2147/amep.s402059","title":"Utilizing Evaluation and Development Frameworks to Engineer a College-Wide Evaluation and Reform of an Undergraduate Dental Curriculum","year":2023,"lang":"en","type":"article","venue":"Advances in Medical Education and Practice","topic":"Innovations in Medical Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"School of Dentistry, University of Maryland; University of Texas Health Science Center at Houston; McGill University; University of Toronto; University of Louisville","keywords":"Operationalization; Curriculum; Optimal distinctiveness theory; Hindsight bias; Medical education; Process (computing); Data collection; Focus group; Dental education; Computer science; Engineering ethics; Psychology; Medicine; Pedagogy; Engineering; Sociology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3086728,0.001755424,0.001548648,0.01057325,0.004514166,0.01516601,0.003596593,0.002030411,0.001767236],"category_scores_gemma":[0.2269491,0.0007487565,0.001468872,0.006370008,0.01025935,0.008425302,0.009432853,0.003375964,0.0003653677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03337535,"about_ca_system_score_gemma":0.06420855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01093492,"about_ca_topic_score_gemma":0.0184761,"domain_scores_codex":[0.6142192,0.3301604,0.01530771,0.006197424,0.03017636,0.00393883],"domain_scores_gemma":[0.7564827,0.1446388,0.01648552,0.01522059,0.06245054,0.004721875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003452549,0.001862705,0.02285837,0.007808393,0.0004790579,0.0005683114,0.03273306,0.01524478,0.003587609,0.2173161,0.01142053,0.6857757],"study_design_scores_gemma":[0.001405139,0.007506393,0.06205146,0.03859463,0.001534126,0.001405176,0.2059289,0.1528616,0.0299305,0.2547687,0.243166,0.0008473287],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1016843,0.005372413,0.7592412,0.02366434,0.000569442,0.03244992,0.0005980112,0.0008453319,0.07557502],"genre_scores_gemma":[0.2713147,0.0008493672,0.7156003,0.0008351445,0.00003910455,0.009444967,0.0002985249,0.00008880912,0.001529208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3086728,"threshold_uncertainty_score":0.8525296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02480308758281099,"score_gpt":0.4467733530268151,"score_spread":0.4219702654440041,"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."}}