{"id":"W2991087363","doi":"10.5194/acp-19-13871-2019","title":"Estimation of NO <sub> <i>x</i> </sub> and SO <sub>2</sub> emissions from Sarnia, Ontario, using a mobile MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) and a NO <sub> <i>x</i> </sub> analyzer","year":2019,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; Environment and Climate Change Canada; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Environment; York University","keywords":"NOx; Pollutant; Differential optical absorption spectroscopy; Environmental science; Atmospheric sciences; Nitrogen oxides; Mixing ratio; Chemistry; Meteorology; Absorption (acoustics); Environmental chemistry; Combustion; Geology; Materials science; Physics; Waste management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001074954,0.0004568811,0.0001301837,0.0003703063,0.0006214671,0.0003874312,0.0003154685,0.0001855124,0.0006729297],"category_scores_gemma":[0.0001352895,0.0002416695,0.0002073071,0.000324789,0.0001681582,0.0002142313,0.0002066885,0.0002019886,0.0002170869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002667384,"about_ca_system_score_gemma":0.002472625,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6020281,"about_ca_topic_score_gemma":0.8356542,"domain_scores_codex":[0.9998733,0.000003178169,0.000003750023,0.00003180796,0.00007343796,0.0000145787],"domain_scores_gemma":[0.9999229,0.00000375696,0.00001473008,0.000002930078,0.00004673947,0.000008911321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003740467,0.0001663649,0.5568252,0.0002428354,0.0001184035,0.0004540409,0.000816528,0.006131809,0.3893054,0.0002581778,0.002112918,0.04319438],"study_design_scores_gemma":[0.00003689706,0.000147199,0.9160861,0.00001778478,0.00007576411,0.00009146473,0.0007663728,0.021649,0.05632579,0.00005216376,0.004720216,0.00003126608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927241,0.00009556625,0.001275823,0.0000399041,0.00000620094,0.00005118143,0.0009538711,0.00006779383,0.004785671],"genre_scores_gemma":[0.9913237,0.0002368061,0.003217684,0.00002690417,0.000003679457,0.00003162974,0.001521039,0.0000160834,0.003622497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3979719,"threshold_uncertainty_score":0.8006312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006087539050885672,"score_gpt":0.1984693001660615,"score_spread":0.1923817611151759,"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."}}