{"id":"W4409799988","doi":"10.11159/iceptp25.141","title":"AI-Enriched Automation for Evaluating Health Risks from Air Pollution","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automation; Air pollution; Pollution; Computer science; Risk analysis (engineering); Environmental science; Engineering; Business; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001444299,0.001097176,0.0005484134,0.0009393879,0.000316978,0.001469505,0.001654526,0.0007207285,0.002471334],"category_scores_gemma":[0.006770966,0.0002828705,0.000727515,0.000417536,0.0005543658,0.001109667,0.001517303,0.0009918999,0.0006962665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007184322,"about_ca_system_score_gemma":0.001079406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006291699,"about_ca_topic_score_gemma":0.002582089,"domain_scores_codex":[0.9986644,0.0003354924,0.0001072813,0.0003356216,0.0004895112,0.00006770446],"domain_scores_gemma":[0.9973072,0.001501861,0.0002537887,0.0004133033,0.0004231602,0.0001006553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006965978,0.0004759258,0.01529723,0.0004781445,0.0002883318,0.0004167069,0.0005530058,0.5225605,0.02511023,0.01405808,0.007077522,0.4129878],"study_design_scores_gemma":[0.0000307891,0.00009615112,0.001582105,0.00002261867,0.00003775911,0.00007561959,0.00003127506,0.9769139,0.008381669,0.009323656,0.003481996,0.0000224876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03486292,0.000279301,0.9439675,0.000308967,0.0000577007,0.0002417709,0.0006511722,0.01583779,0.003792908],"genre_scores_gemma":[0.6788646,0.0001853546,0.3173783,0.00028793,0.00007257512,0.0003052268,0.00102807,0.0003240544,0.001553812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006291699,"threshold_uncertainty_score":0.01251012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01862337783433458,"score_gpt":0.282552654447462,"score_spread":0.2639292766131274,"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."}}