{"id":"W2740827051","doi":"10.2196/humanfactors.6857","title":"Modeling Patient Treatment With Medical Records: An Abstraction Hierarchy to Understand User Competencies and Needs","year":2017,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Conestoga College","funders":"","keywords":"Sociotechnical system; Abstraction; Hierarchy; Scope (computer science); Work (physics); Computer science; Domain (mathematical analysis); Health care; Knowledge management; Psychology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00911865,0.0009428487,0.0004833178,0.004262867,0.001930964,0.004249782,0.00168327,0.001241764,0.00228808],"category_scores_gemma":[0.023874,0.0007890294,0.002184621,0.00284328,0.002465324,0.008696532,0.003529939,0.001762233,0.0004879811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003881264,"about_ca_system_score_gemma":0.005405608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02332276,"about_ca_topic_score_gemma":0.02482311,"domain_scores_codex":[0.9899441,0.007006504,0.0007914715,0.0007739943,0.001179799,0.0003041337],"domain_scores_gemma":[0.9824955,0.01242017,0.001269444,0.001659859,0.001731918,0.0004230476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003598216,0.000684813,0.09437463,0.001806707,0.0004497384,0.001491464,0.1147207,0.2188285,0.006873803,0.3143343,0.006774798,0.2393006],"study_design_scores_gemma":[0.00005369146,0.0001762269,0.01073545,0.0007771545,0.0002970058,0.0004671942,0.02096788,0.7560238,0.002826242,0.1682393,0.03931862,0.0001173949],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1089527,0.0003723793,0.8729976,0.003379665,0.00002558462,0.001095749,0.001100563,0.0008302073,0.01124549],"genre_scores_gemma":[0.3737412,0.0002265692,0.6227791,0.0001754682,0.00001334677,0.0005856334,0.001172057,0.00007191985,0.001234716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02332276,"threshold_uncertainty_score":0.04822457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0652248373115682,"score_gpt":0.3413551814976708,"score_spread":0.2761303441861026,"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."}}