{"id":"W2091285062","doi":"10.1007/s00038-006-6052-z","title":"Gender-based analysis, women’s health surveillance and women’s health indicators – Working together to promote equity in health in Canada","year":2007,"lang":"en","type":"article","venue":"Sozial- und Präventivmedizin","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Canada","funders":"Health Canada; Public Health Agency of Canada","keywords":"Health equity; Public health; Social determinants of health; Population health; Health policy; Health indicator; Environmental health; Health promotion; Equity (law); Psychological intervention; Race and health; Population; Economic growth; Medicine; Political science; Public economics; Nursing; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.02024535,0.0003054106,0.001142433,0.001007879,0.0006848008,0.00009801274,0.0004058096,0.0001326212,0.0002003135],"category_scores_gemma":[0.0003372791,0.0003260301,0.00007467785,0.003724899,0.0001380899,0.0001098949,0.0001300019,0.0005106768,0.000003344303],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.02198922,"about_ca_system_score_gemma":0.02178883,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9638337,"about_ca_topic_score_gemma":0.9987933,"domain_scores_codex":[0.9921079,0.001360887,0.001438801,0.0007322319,0.001012129,0.003348034],"domain_scores_gemma":[0.9965308,0.0004297531,0.0005872248,0.0003354361,0.00003786582,0.002078942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008567143,0.0001216494,0.867882,0.0004227333,0.00005842205,0.00001306182,0.04858815,0.00008251783,2.006729e-7,0.001094512,0.0006663274,0.08098475],"study_design_scores_gemma":[0.0008163719,0.0001289757,0.8417917,0.0001807981,0.00000277262,2.144823e-7,0.01971392,0.00002913725,0.000001474982,0.0004753376,0.1365374,0.0003219696],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9497868,0.003479245,0.0004078445,0.04336529,0.0007229074,0.001522219,0.00006670653,0.00005694981,0.0005920601],"genre_scores_gemma":[0.9716038,0.0006483796,0.0004361163,0.02686748,0.0001682865,0.0001091029,0.00002335336,0.00002932692,0.0001141812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.135871,"threshold_uncertainty_score":0.9999192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04426111354643875,"score_gpt":0.3925645650323557,"score_spread":0.3483034514859169,"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."}}