{"id":"W3092288994","doi":"10.2196/20050","title":"An Environmental Scan of Sex and Gender in Electronic Health Records: Analysis of Public Information Sources","year":2020,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Sex and Gender in Healthcare","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Health Infoway; University of Victoria","funders":"Canadian Institutes of Health Research","keywords":"Health records; Public health; Computer science; Psychology; Medicine; Environmental health; Internet privacy; Political science; Health care; Nursing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02898783,0.0004198454,0.0004884315,0.01726836,0.002380328,0.00453101,0.0009990603,0.0006458705,0.001736989],"category_scores_gemma":[0.1414877,0.0004478895,0.001037268,0.04210307,0.002948054,0.003772737,0.0063074,0.000793046,0.0002603251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006995089,"about_ca_system_score_gemma":0.01185319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0928468,"about_ca_topic_score_gemma":0.07778347,"domain_scores_codex":[0.9319271,0.02600048,0.007349126,0.004213395,0.02809032,0.002419551],"domain_scores_gemma":[0.6880119,0.1889939,0.0452462,0.01529987,0.06115256,0.001295496],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001583808,0.00005486856,0.913058,0.0008803493,0.0002289188,0.0005917142,0.04813659,0.0003437193,0.0006137571,0.004074003,0.001802283,0.03005744],"study_design_scores_gemma":[0.00001405821,0.00008350106,0.8860765,0.001144456,0.0002703588,0.0005560761,0.07682746,0.001485385,0.00165867,0.001144617,0.03067909,0.00005994703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683289,0.001028194,0.005443407,0.001049561,0.0000229384,0.0004671259,0.01170546,0.00008763259,0.01186683],"genre_scores_gemma":[0.9841211,0.0005134441,0.007170333,0.0002681624,0.00002679973,0.0005538625,0.006593445,0.00008736274,0.0006654896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9710122,"threshold_uncertainty_score":0.1846128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1560002677922473,"score_gpt":0.455926893621563,"score_spread":0.2999266258293157,"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."}}