{"id":"W2193026706","doi":"10.1007/978-3-319-12307-3_15","title":"Accounting for Temperature when Modeling Population Health Risk Due to Air Pollution","year":2015,"lang":"en","type":"book-chapter","venue":"Springer proceedings in mathematics & statistics","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Econometrics; Context (archaeology); Parametric statistics; Lag; Parametric model; Population health; Population; Environmental science; Generalized additive model; Air pollution; Statistics; Environmental health; Mathematics; Computer science; Geography; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001619635,0.0004572542,0.0006969586,0.0002180737,0.0002685351,0.0001071713,0.0002652743,0.000345267,0.0001303619],"category_scores_gemma":[0.000585458,0.0004701167,0.00005847388,0.00007461202,0.00003389705,0.0002188423,0.0002213882,0.000545924,0.0001238893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00151772,"about_ca_system_score_gemma":0.00006313347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000502395,"about_ca_topic_score_gemma":0.0008538894,"domain_scores_codex":[0.9971741,0.000005670236,0.0009706337,0.0005606336,0.0006046246,0.0006843531],"domain_scores_gemma":[0.9984468,0.00007246647,0.0007955917,0.0002056208,0.0001355003,0.0003440786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003852141,0.000656084,0.00444037,0.022567,0.0001558698,0.00003584326,0.1198357,0.04302286,0.000336321,0.3825882,0.3517482,0.07422826],"study_design_scores_gemma":[0.0005464935,0.0002549903,0.000676123,0.002183314,0.00008748934,0.00001553016,0.0005202799,0.0655946,0.000005406051,0.9141887,0.01501559,0.0009114164],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1493538,0.003323295,0.5510712,0.01845233,0.004707705,0.04734746,0.01684493,0.002010091,0.2068892],"genre_scores_gemma":[0.04429888,0.0006091924,0.9264691,0.002549999,0.001013795,0.0002397103,0.0004858219,0.0005073635,0.02382614],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5316005,"threshold_uncertainty_score":0.9997751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06252342853479183,"score_gpt":0.3188625304366826,"score_spread":0.2563391019018908,"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."}}