{"id":"W2921218787","doi":"","title":"Measuring International Health Inequalities and Socioeconomic Status Using Household Survey Data","year":2019,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Socioeconomic status; Inequality; Survey research; Sociology; Geography; Socioeconomics; Demography; Mathematics; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009091764,0.0002142154,0.0004092672,0.0001679798,0.0005706604,0.0002206515,0.0007050572,0.0002369975,0.009511479],"category_scores_gemma":[0.00007982504,0.0002695968,0.00005140281,0.0001167256,0.00008810902,0.0006832983,0.0002262347,0.0002919472,0.00001890044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008990536,"about_ca_system_score_gemma":0.00174707,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1615458,"about_ca_topic_score_gemma":0.2516452,"domain_scores_codex":[0.9978117,0.0005009791,0.0002914012,0.0004994614,0.00031489,0.000581597],"domain_scores_gemma":[0.9987702,0.0002362987,0.0003531944,0.0003009094,0.00008267923,0.0002567584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003406953,0.00007232549,0.710699,0.001651187,0.0003961301,0.00001968035,0.04448832,0.0001024667,0.00000162918,0.01120635,0.004113968,0.2269082],"study_design_scores_gemma":[0.0007547201,0.00002076576,0.1558279,0.0003410015,0.00004344377,5.064256e-7,0.1402835,0.0002760181,0.000001013775,0.00005231548,0.7018698,0.0005289406],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.4273517,0.002111754,0.0001503792,0.001495555,0.006985675,0.001082835,0.004213938,0.0002037633,0.5564044],"genre_scores_gemma":[0.2135712,0.004588319,0.0004542101,0.001132241,0.0004446241,6.583931e-7,0.0034839,0.00008572892,0.7762392],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6977559,"threshold_uncertainty_score":0.9999756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1692892746913033,"score_gpt":0.3298533891904454,"score_spread":0.1605641144991421,"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."}}