{"id":"W2072652148","doi":"10.3390/ijerph10115750","title":"Simulation Models for Socioeconomic Inequalities in Health: A Systematic Review","year":2013,"lang":"en","type":"review","venue":"International Journal of Environmental Research and Public Health","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Socioeconomic status; Inequality; Simulation modeling; Psychological intervention; Social determinants of health; Computer science; Social inequality; Poison control; Multilevel model; Environmental health; Management science; Psychology; Public health; Medicine; Mathematics; Engineering; Machine learning; Population; Mathematical economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03368602,0.0002049251,0.001939299,0.001623531,0.0001354179,0.0004205033,0.0009612591,0.0001131648,0.0001349157],"category_scores_gemma":[0.003418729,0.0001410762,0.0003569542,0.0002112942,0.0001263648,0.0008204761,0.000136325,0.0005452193,0.00004077151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001081685,"about_ca_system_score_gemma":0.001211527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007780874,"about_ca_topic_score_gemma":0.00002001758,"domain_scores_codex":[0.9903103,0.002294,0.004235383,0.0003499241,0.002336272,0.0004741904],"domain_scores_gemma":[0.9892551,0.006867647,0.002832867,0.0002548055,0.0003707395,0.0004188571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000918963,0.0002336004,0.000007183508,0.1621192,0.0001380646,0.000002311144,0.0004620052,0.0004211385,1.519575e-8,0.001540726,0.0008302309,0.8342363],"study_design_scores_gemma":[0.001013318,0.001181914,0.00001293312,0.4036747,0.00004682413,0.0001227007,0.004024993,0.04428272,8.032366e-9,0.06761991,0.4776029,0.0004171216],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004547619,0.9875329,0.005279574,0.004843014,0.0002057354,0.001883829,0.0001822174,0.000002981145,0.00002430393],"genre_scores_gemma":[0.00291898,0.9955891,0.0003250054,0.0005938797,0.0001175425,0.0001513217,0.00007011007,0.00002080486,0.0002132809],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8338192,"threshold_uncertainty_score":0.9950236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.601529136579556,"score_gpt":0.5650477430052004,"score_spread":0.03648139357435554,"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."}}