{"id":"W3003985767","doi":"10.23889/ijpds.v5i1.1123","title":"Unlocking the Potential of Electronic Health Records for Health Research","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health; University of Calgary; Alberta Health Services","funders":"","keywords":"Health records; Electronic health record; Data science; Computer science; Health care; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.02713268,0.0001125406,0.0002904126,0.0003178176,0.003390721,0.00008940218,0.003040363,0.00006132835,0.0000417853],"category_scores_gemma":[0.00481846,0.00008435882,0.00007128641,0.0007369192,0.000155703,0.0009225232,0.0004307048,0.001072049,0.00001019731],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00174989,"about_ca_system_score_gemma":0.01092163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001954107,"about_ca_topic_score_gemma":0.001173518,"domain_scores_codex":[0.9939699,0.000888394,0.001557803,0.0004913578,0.001785662,0.001306858],"domain_scores_gemma":[0.9945871,0.001061259,0.001417792,0.0004752963,0.00207744,0.000381102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002305965,0.0002626245,0.04335991,0.001525494,0.000247937,0.000002323192,0.009964,0.00275559,0.001800962,0.2013156,0.4163315,0.3201281],"study_design_scores_gemma":[0.0029119,0.002226975,0.02410724,0.0008204032,0.00001188728,0.00005785343,0.00386388,0.2601083,0.0000293339,0.01512393,0.6904693,0.0002690003],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06527045,0.001530677,0.3414319,0.5707458,0.01258042,0.006760231,0.001417729,0.0000834045,0.0001794404],"genre_scores_gemma":[0.986845,0.0004035576,0.003338335,0.005875341,0.002939853,0.00009062278,0.0003093685,0.00002652409,0.0001714337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9215745,"threshold_uncertainty_score":0.9979067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4504956564272377,"score_gpt":0.6276072710141566,"score_spread":0.1771116145869189,"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."}}