{"id":"W2513410927","doi":"10.1016/j.contraception.2015.06.075","title":"Accuracy of surgical abortion data capture in Canadian Government Health Administration Databases","year":2015,"lang":"en","type":"article","venue":"Contraception","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Abortion; Population; Clinical trial; Reproductive health; Coding (social sciences); Medical record; Database; Medical emergency; Environmental health; Pregnancy; Statistics; Surgery","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":[],"consensus_categories":[],"category_scores_codex":[0.0009631888,0.00008029582,0.0001583505,0.00004969616,0.00003308943,0.00001352582,0.00009612194,0.00005117819,0.00006105586],"category_scores_gemma":[0.000612311,0.00007977422,0.00001508643,0.0001149234,0.0000159039,0.0004001165,0.00001897251,0.00007923615,0.000006435139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003927089,"about_ca_system_score_gemma":0.000533272,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07230104,"about_ca_topic_score_gemma":0.583801,"domain_scores_codex":[0.9988226,0.00009671527,0.0004263163,0.000171471,0.0003128082,0.0001700386],"domain_scores_gemma":[0.9989668,0.0001134868,0.000287547,0.0003804711,0.00007112439,0.0001806365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007793567,0.001322972,0.3685878,0.0006708428,0.00005574309,0.00008714551,0.005270065,0.001081554,0.0004850173,0.3324632,0.08933677,0.1998595],"study_design_scores_gemma":[0.007815155,0.0004832549,0.5137954,0.0007245434,0.0001012721,0.0001581788,0.002504516,0.1607796,0.0004771465,0.01296413,0.2992567,0.0009401648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775151,0.0005780397,0.01028078,0.00733678,0.0003998048,0.001034367,0.001421596,0.00005188634,0.001381648],"genre_scores_gemma":[0.9957966,0.00005786202,0.002125038,0.00004348951,0.00007818448,0.000006909817,0.001841027,0.000007795386,0.00004313353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5114999,"threshold_uncertainty_score":0.9338766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1801915940743374,"score_gpt":0.4157600104456439,"score_spread":0.2355684163713065,"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."}}