{"id":"W6903014086","doi":"10.1021/acs.est.9b04488.s001","title":"Enhanced\\nCapabilities of TROPOMI NO<sub>2</sub>: Estimating\\nNO<sub><i>X</i></sub> from North American Cities and Power\\nPlants","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Megacity; Troposphere; Air pollution; Air mass (solar energy); Greenhouse gas","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005115945,0.0008450244,0.0002805713,0.00102813,0.0005281531,0.001029972,0.000749037,0.0004299884,0.001278032],"category_scores_gemma":[0.001749396,0.000554333,0.0005940362,0.002207717,0.0003259705,0.001056726,0.000841616,0.0005900043,0.0004464141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007647218,"about_ca_system_score_gemma":0.001321197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1698326,"about_ca_topic_score_gemma":0.2418045,"domain_scores_codex":[0.9995865,0.00004921363,0.00002130246,0.0001594643,0.000112415,0.0000710515],"domain_scores_gemma":[0.9995728,0.00008998594,0.00005892087,0.0001359621,0.0001191296,0.00002317475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002916513,0.0001733087,0.7118451,0.0002770521,0.0005680182,0.0004873846,0.0008107347,0.1197091,0.04432812,0.002754935,0.01003797,0.1087167],"study_design_scores_gemma":[0.00006841858,0.00002929263,0.7843916,0.00006017443,0.0001724968,0.0001205856,0.0003192241,0.1804407,0.02098621,0.0008609209,0.01245705,0.00009325047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9518826,0.0005218789,0.02511526,0.0003101531,0.00007739472,0.00007505598,0.009037551,0.000855978,0.01212412],"genre_scores_gemma":[0.9678524,0.0003285907,0.01913868,0.0001276799,0.0000435281,0.00009882317,0.01034853,0.000276614,0.001785099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1698326,"threshold_uncertainty_score":0.3376882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01001700051373012,"score_gpt":0.1964789477223239,"score_spread":0.1864619472085938,"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."}}