{"id":"W4413268320","doi":"10.1016/j.atherosclerosis.2025.120344","title":"Geospatial clustering of autoantibodies against apolipoprotein A-1 and environmental pollution in the Geneva general population","year":2025,"lang":"en","type":"article","venue":"Atherosclerosis","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Population and Public Health","funders":"","keywords":"Geospatial analysis; Autoantibody; Cluster analysis; Population; Environmental pollution; Pollution; Geography; Environmental health; Medicine; Biology; Computer science; Immunology; Environmental protection; Cartography; Antibody; Ecology; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0005111416,0.0001536116,0.0001618991,0.00005952294,0.0001756615,0.00002101296,0.0001592597,0.0000787422,0.00007886035],"category_scores_gemma":[0.00002566071,0.0001319982,0.00004211336,0.0001551515,0.0001899588,0.0001733843,0.0002038795,0.0001340841,0.00001411193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002287983,"about_ca_system_score_gemma":0.000004778201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004192695,"about_ca_topic_score_gemma":0.001226626,"domain_scores_codex":[0.9985987,0.000195129,0.0003145936,0.0003616048,0.0002548536,0.0002751408],"domain_scores_gemma":[0.9995565,0.00004106834,0.0001097951,0.0002572869,9.988845e-7,0.00003430772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001897031,0.0001081673,0.8065509,0.00002264312,0.00001083697,6.578031e-7,0.001610697,0.003573152,0.1316825,0.00006516842,0.00003554158,0.05632069],"study_design_scores_gemma":[0.0003812656,0.00003784165,0.9843217,0.00004711376,0.00001225485,6.303839e-7,0.0003414625,0.01182987,0.002555567,0.0001471385,0.0002083013,0.0001169083],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966939,0.00006738747,0.001485192,0.0005012293,0.00005434933,0.0004898417,0.00002387595,0.00001418233,0.0006700606],"genre_scores_gemma":[0.9978963,0.0002502102,0.0007702659,0.0009137267,0.00002268468,0.00004353246,0.00002260606,0.00001233023,0.00006840661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1777707,"threshold_uncertainty_score":0.6338128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000135762655232,"score_gpt":0.2354665498052247,"score_spread":0.2254651921786724,"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."}}