{"id":"W1484732272","doi":"10.2478/s13382-011-0034-y","title":"Case-crossover design: Air pollution and health outcomes","year":2011,"lang":"en","type":"article","venue":"International Journal of Occupational Medicine and Environmental Health","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Population and Public Health; Health Canada","funders":"Health Canada","keywords":"Air pollution; Conditional logistic regression; Crossover study; Nitrogen dioxide; Environmental health; Emergency department; Logistic regression; Statistics; Depression (economics); Environmental science; Medicine; Demography; Mathematics; Meteorology; Geography; Population; Biology; Psychiatry; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009733434,0.0001172578,0.0002915756,0.000125367,0.00009848076,0.000006817502,0.00008211189,0.00003320205,0.0002465766],"category_scores_gemma":[0.0002466612,0.00008359995,0.00003146741,0.00002827655,0.0001841467,0.0001246238,0.00003917082,0.0001448118,0.000001314048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001617021,"about_ca_system_score_gemma":0.00008767772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002079931,"about_ca_topic_score_gemma":0.000009780377,"domain_scores_codex":[0.9985359,0.0001232442,0.0006370101,0.0001203325,0.0004444311,0.0001391271],"domain_scores_gemma":[0.9987819,0.0003874377,0.0005085001,0.00005794438,0.00003836491,0.0002258145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002172793,0.001464822,0.2713951,0.0002624049,0.0007533658,0.00134381,0.02072888,0.00002209337,0.0001081113,0.2435308,0.02688379,0.431334],"study_design_scores_gemma":[0.002565553,0.001950372,0.8700132,0.0002635706,0.00003011157,0.008096474,0.001604114,0.0004118373,0.00002738305,0.1141461,0.0007238202,0.0001675521],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4986637,0.001375903,0.4786618,0.01917958,0.001217982,0.0004028952,0.0001977148,0.00001788225,0.0002824912],"genre_scores_gemma":[0.8635197,0.0004439293,0.1315209,0.004326371,0.0001471018,0.000001911414,0.000005384763,0.000007937107,0.00002681357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.598618,"threshold_uncertainty_score":0.3409107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3376993523242523,"score_gpt":0.4705930407401628,"score_spread":0.1328936884159105,"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."}}