{"id":"W2914621426","doi":"10.1289/isee.2013.o-1-11-02","title":"Assessing the Air Quality Health Benefits of Location-Specific Emission Controls: A Source Attribution Study using Adjoint Sensitivity Analysis","year":2013,"lang":"en","type":"article","venue":"ISEE Conference Abstracts","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"CMAQ; Air quality index; Environmental science; Air pollution; Pollutant; NOx; Work (physics); Attribution; Health effect; Environmental health; Meteorology; Environmental resource management; Geography; Engineering; Medicine; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006926122,0.001143246,0.0006637799,0.002340358,0.0004612957,0.001027828,0.001098376,0.001383142,0.001781421],"category_scores_gemma":[0.01275728,0.0004076,0.003305618,0.001184419,0.0007897414,0.001176152,0.001438263,0.001051082,0.00008446826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001711531,"about_ca_system_score_gemma":0.0008190383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01582564,"about_ca_topic_score_gemma":0.005173387,"domain_scores_codex":[0.9980627,0.001316939,0.00006511348,0.0002323342,0.0001959493,0.000126995],"domain_scores_gemma":[0.9799899,0.01751266,0.0008912019,0.0008565407,0.0005880314,0.0001616534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001045951,0.0006855446,0.04614419,0.0001959988,0.0009260114,0.0004036742,0.0001245175,0.9306387,0.003919743,0.004276112,0.0003531787,0.01128641],"study_design_scores_gemma":[0.0001124727,0.0003716388,0.01645378,0.00002749768,0.0003102155,0.0000990511,0.0001343855,0.9749568,0.002385967,0.004800916,0.0002826327,0.00006462052],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678947,0.0002607331,0.02928318,0.0001630321,0.0000308156,0.0001618075,0.000473136,0.00007610964,0.001656433],"genre_scores_gemma":[0.9970888,0.00004163848,0.002534343,0.00001765756,0.000005919293,0.00004675663,0.000105003,0.000008779951,0.0001510336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01582564,"threshold_uncertainty_score":0.03662926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1598268098402985,"score_gpt":0.3888628078906132,"score_spread":0.2290359980503147,"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."}}