{"id":"W1957814736","doi":"10.1007/s10874-015-9319-z","title":"Toxic volatile organic air pollutants across Canada: multi-year concentration trends, regional air quality modelling and source apportionment","year":2015,"lang":"en","type":"article","venue":"Journal of Atmospheric Chemistry","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Armed Forces","funders":"Health Canada; U.S. Environmental Protection Agency","keywords":"Air quality index; Environmental science; Benzene; CMAQ; Air pollution; Petrochemical; Volatile organic compound; Formaldehyde; Acetaldehyde; Pollutant; Pollution; NOx; Environmental chemistry; Emission inventory; Atmospheric sciences; Meteorology; Chemistry; Combustion; Environmental engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003980612,0.0002081034,0.0003242762,2.839014e-7,0.0001489523,0.00003645429,0.0001977294,0.000120768,0.0008325134],"category_scores_gemma":[0.00005745288,0.0001836537,0.00007538646,0.0001894345,0.0001042157,0.0002266367,0.00001905298,0.0002846912,0.000002516604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009077437,"about_ca_system_score_gemma":0.000739583,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01296076,"about_ca_topic_score_gemma":0.004893313,"domain_scores_codex":[0.9981563,0.00003335066,0.0006410999,0.0002383049,0.000596748,0.0003341732],"domain_scores_gemma":[0.9985282,0.00005823448,0.0006437218,0.0001590258,0.000129805,0.0004810161],"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":[0.0009341797,0.0002824593,0.3150981,0.0002324049,0.0003454605,0.0002034749,0.002817454,0.5950987,0.0442928,0.000001525096,0.005678614,0.03501482],"study_design_scores_gemma":[0.01290509,0.0004375605,0.3832308,0.0004090687,0.0002595307,0.002510411,0.02827139,0.4519687,0.08583225,0.0001639256,0.03127699,0.002734278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991634,0.0008421244,0.006651447,0.0003220374,0.0001400669,0.00003789093,0.00003679652,0.00001499443,0.0003206267],"genre_scores_gemma":[0.9915874,0.00005443683,0.006367921,0.0001599777,0.0002711346,2.888637e-7,0.00002428745,0.000007699721,0.001526849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.14313,"threshold_uncertainty_score":0.993612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02770509015718957,"score_gpt":0.2392854866250506,"score_spread":0.2115803964678611,"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."}}