{"id":"W2079396669","doi":"10.5194/acp-9-1017-2009","title":"Investigation of NO <sub>x</sub> emissions and NO <sub>x</sub> -related chemistry in East Asia using CMAQ-predicted and GOME-derived NO <sub>2</sub> columns","year":2009,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Korea Science and Engineering Foundation; Ministry of Environment","keywords":"CMAQ; Isoprene; NOx; Atmospheric sciences; Aerosol; Chemistry; Emission inventory; Environmental science; Climatology; Air quality index; Meteorology; Environmental chemistry; Geography; Physics; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003806101,0.0005183719,0.0002097795,0.0002564877,0.0001884435,0.0004568674,0.0003080886,0.0002688473,0.0002369003],"category_scores_gemma":[0.0002511899,0.0002570341,0.0003803344,0.0002802337,0.0001599581,0.0006713083,0.0002138922,0.0002042923,0.00007583422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005461401,"about_ca_system_score_gemma":0.0004533223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02685069,"about_ca_topic_score_gemma":0.02545477,"domain_scores_codex":[0.9999176,0.00001043186,0.000007803827,0.00003383469,0.00001778418,0.00001255306],"domain_scores_gemma":[0.9997762,0.00004853042,0.00005979177,0.00001997272,0.00007508571,0.00002041885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000270474,0.0001621451,0.8820439,0.0001758508,0.0003736819,0.0002929236,0.0002491636,0.03501834,0.07099088,0.0002167839,0.0001398928,0.01006605],"study_design_scores_gemma":[0.00002584251,0.0001725981,0.8159529,0.00001978611,0.0002427599,0.0000915722,0.0005124957,0.1302585,0.05172973,0.0001213181,0.0008464833,0.00002599003],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989209,0.00008976549,0.0005291832,0.00001259967,0.000003018831,0.000004697928,0.0001597946,0.00001137458,0.0002686878],"genre_scores_gemma":[0.9986046,0.00009558813,0.0008563951,0.00001655807,0.00000188616,0.000003539897,0.0002984093,0.000005666988,0.0001173305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02685069,"threshold_uncertainty_score":0.05338883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008184712248487528,"score_gpt":0.1843318004829675,"score_spread":0.17614708823448,"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."}}