{"id":"W2908889590","doi":"10.1029/2018jd028670","title":"Quantifying Emissions of CO and NO<sub>x</sub> Using Observations From MOPITT, OMI, TES, and OSIRIS","year":2019,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Environment and Climate Change Canada; Carleton University; University of Toronto","funders":"Environment and Climate Change Canada; National Aeronautics and Space Administration","keywords":"Troposphere; Stratosphere; Environmental science; Atmospheric sciences; Ozone; Data assimilation; Ozone Monitoring Instrument; Climatology; Osiris; Microwave Limb Sounder; Latitude; Northern Hemisphere; Seasonality; Meteorology; Geography; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004397515,0.0003956174,0.0003029803,0.0004180931,0.0002916299,0.0004367599,0.0003718295,0.0003753139,0.0002584254],"category_scores_gemma":[0.0005725411,0.0003014096,0.0004285288,0.0003862094,0.0001882135,0.0005274812,0.0003295763,0.0002717781,0.00008509003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006138822,"about_ca_system_score_gemma":0.0003215166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02471858,"about_ca_topic_score_gemma":0.0444058,"domain_scores_codex":[0.9998555,0.00002319594,0.000008022605,0.0000520715,0.00003933867,0.00002187435],"domain_scores_gemma":[0.9997998,0.00003834596,0.00005820417,0.00002787412,0.00005172882,0.00002414826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007457888,0.00029184,0.6109275,0.0001143003,0.0008233209,0.0002671905,0.0002451462,0.2205496,0.1350683,0.0004130475,0.001483864,0.02907019],"study_design_scores_gemma":[0.0000555625,0.00009487233,0.5319569,0.00001247777,0.0001640182,0.00005170763,0.00009665915,0.4326915,0.03335097,0.0001602537,0.001322333,0.00004285519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976826,0.00002789244,0.00121972,0.00002628013,0.00000489765,0.000008164863,0.0006233386,0.00008667618,0.0003204073],"genre_scores_gemma":[0.9935055,0.00002447858,0.004808683,0.00001348498,0.00000586862,0.00001138642,0.001508106,0.00001784521,0.0001046749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02471858,"threshold_uncertainty_score":0.04914939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05525155783377041,"score_gpt":0.3127338394706261,"score_spread":0.2574822816368557,"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."}}