{"id":"W4411772313","doi":"10.21203/rs.3.rs-6769454/v1","title":"The engagement equation: A model for understanding what drives physician engagement with data-driven clinical performance feedback","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais; Women's College Hospital; University of Toronto; Trillium Health Centre","funders":"Canadian Institutes of Health Research","keywords":"Structural equation modeling; Psychology; Computer science; Data science; Medical education; Medicine; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01057853,0.0009372141,0.00107484,0.001401426,0.0008684302,0.004181265,0.001587951,0.003175512,0.02152161],"category_scores_gemma":[0.07590436,0.0007053273,0.001084546,0.00160891,0.00212866,0.007782289,0.002466152,0.004719744,0.003113865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00272193,"about_ca_system_score_gemma":0.004338328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01023245,"about_ca_topic_score_gemma":0.005487343,"domain_scores_codex":[0.9925841,0.003995889,0.0003203767,0.001073728,0.001180938,0.0008449968],"domain_scores_gemma":[0.9316777,0.06044302,0.003329465,0.001067897,0.002477951,0.00100392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007023344,0.001630471,0.1623879,0.0005915955,0.0003434151,0.0003551234,0.008669089,0.09016096,0.001995294,0.5720669,0.01703224,0.1440646],"study_design_scores_gemma":[0.0002558173,0.0005976091,0.03891218,0.000431549,0.0002200842,0.0002266574,0.00391301,0.5856339,0.001234621,0.3555312,0.01289271,0.0001506941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3760441,0.0007249058,0.5080482,0.03977322,0.0003351014,0.0010146,0.00300979,0.0006225955,0.07042746],"genre_scores_gemma":[0.9508882,0.0003468902,0.02798798,0.0009841433,0.0001255953,0.0007688978,0.0005613167,0.0001097705,0.01822719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02152161,"threshold_uncertainty_score":0.07199693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6813452718261498,"score_gpt":0.6042117506980476,"score_spread":0.07713352112810223,"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."}}