{"id":"W2962557941","doi":"10.5194/acp-20-99-2020","title":"A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide","year":2020,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"U.S. Environmental Protection Agency; National Aeronautics and Space Administration","keywords":"NOx; Ozone Monitoring Instrument; Nitrogen dioxide; Environmental science; Ozone; Emission inventory; Coal; Carbon dioxide; Atmospheric sciences; Satellite; Power station; Air quality index; Nitrogen oxide; Greenhouse gas; Meteorology; Combustion; Waste management; Chemistry; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007471334,0.0002615078,0.0003796234,9.924413e-8,0.00009576777,0.000009089379,0.0002092232,0.0001351833,0.000582502],"category_scores_gemma":[0.00004030338,0.000270476,0.00007962297,0.0002051039,0.0003315972,0.00007599188,0.0001725421,0.0001706328,0.000009398729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009438737,"about_ca_system_score_gemma":0.00002160745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000783567,"about_ca_topic_score_gemma":0.000002408318,"domain_scores_codex":[0.9986387,0.00006174896,0.0003291947,0.0004624338,0.0002168901,0.0002910076],"domain_scores_gemma":[0.9990912,0.0001587028,0.0001473518,0.0002576561,0.0000052267,0.0003398469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006364859,0.00006504365,0.1524023,0.00001483099,0.00006360964,0.00001062205,0.001106621,0.01916373,0.8205567,0.000003580864,0.00002674866,0.006522572],"study_design_scores_gemma":[0.002433239,0.0002400396,0.1842443,0.0001559625,0.000401583,0.00004872681,0.004578613,0.2470287,0.5479003,0.003527135,0.007358545,0.002082907],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778898,0.00008720641,0.02051355,0.0001261285,0.00002108148,0.0001548387,0.00006618036,0.0000375054,0.001103669],"genre_scores_gemma":[0.7801459,0.0000675857,0.2189854,0.000537472,0.00004806477,0.000007744908,0.00004685855,0.00002874972,0.0001322404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2726564,"threshold_uncertainty_score":0.9999747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03568010946961243,"score_gpt":0.2493336952457927,"score_spread":0.2136535857761803,"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."}}