{"id":"W2046214763","doi":"10.1111/j.1365-2753.2005.00594.x","title":"Assessing the impact of clinical information‐retrieval technology in a family practice residency","year":2005,"lang":"en","type":"article","venue":"Journal of Evaluation in Clinical Practice","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"","keywords":"Calculator; Medicine; Clinical decision support system; Clinical Practice; Guideline; MEDLINE; Recall; Family medicine; Decision support system; Computer science; Artificial intelligence; Psychology; Pathology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02082375,0.0006940793,0.0009986365,0.007618066,0.000789073,0.0016123,0.0008258916,0.0009524299,0.003031345],"category_scores_gemma":[0.101938,0.0004019971,0.00158588,0.004979549,0.001011324,0.002187527,0.002344747,0.0005290196,0.0004507038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002110773,"about_ca_system_score_gemma":0.003667939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001751955,"about_ca_topic_score_gemma":0.00198399,"domain_scores_codex":[0.9717203,0.01397573,0.004407047,0.001022871,0.008089371,0.0007846991],"domain_scores_gemma":[0.8935453,0.0644436,0.03055991,0.002023176,0.007015222,0.002412759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002582998,0.002823668,0.8956774,0.002111383,0.000509159,0.0001789091,0.002611008,0.0004720909,0.0005852677,0.00007257525,0.0003036097,0.09207191],"study_design_scores_gemma":[0.0004555725,0.02035017,0.9722409,0.0006519545,0.0005797451,0.0003911425,0.001536869,0.0007930276,0.001648634,0.0001089292,0.001186426,0.00005669894],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994387,0.001584307,0.0006961134,0.0002726888,0.00001388233,0.001248559,0.0003295591,0.00001748874,0.001450367],"genre_scores_gemma":[0.991545,0.001206843,0.005116009,0.0001523137,0.00006332694,0.001354991,0.0002741042,0.000005234517,0.0002823092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02082375,"threshold_uncertainty_score":0.1101278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5063222787653403,"score_gpt":0.7494993036168807,"score_spread":0.2431770248515404,"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."}}