{"id":"W2581041139","doi":"","title":"Constraining CO Emissions Using MOPITT, TES, and OMI Satellite Retrievals","year":2014,"lang":"en","type":"article","venue":"2014 AGU Fall Meeting","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Environmental science; Satellite; Remote sensing; Meteorology; Climatology; Atmospheric sciences; Geography; 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":[0.0007485953,0.001195936,0.00097482,0.001249836,0.0008004405,0.001512733,0.0008301886,0.001264674,0.001450768],"category_scores_gemma":[0.001730413,0.0005795808,0.0010192,0.001931,0.0004300694,0.001605562,0.0008493614,0.0008614517,0.0007670365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006603697,"about_ca_system_score_gemma":0.001412042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04115576,"about_ca_topic_score_gemma":0.0647755,"domain_scores_codex":[0.9996191,0.00004393454,0.00001637267,0.0001354295,0.0001066504,0.00007854648],"domain_scores_gemma":[0.999564,0.00011036,0.00004581332,0.0001003347,0.0001308529,0.00004876217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001381562,0.0006527231,0.151641,0.0005885703,0.001530206,0.0005198407,0.0003896859,0.4964482,0.157943,0.004842369,0.01965673,0.1644061],"study_design_scores_gemma":[0.0004017034,0.0001052562,0.1074657,0.00006106289,0.0004755227,0.00008773054,0.0001636645,0.8438913,0.03351982,0.002731717,0.01096032,0.0001361215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9392545,0.001091866,0.02494635,0.0008047944,0.0002116146,0.00009874789,0.01478222,0.004005772,0.01480419],"genre_scores_gemma":[0.9607926,0.000230161,0.02804225,0.000162778,0.0001192851,0.00006541683,0.00897672,0.0004346239,0.001176186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04115576,"threshold_uncertainty_score":0.08183241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123708229642967,"score_gpt":0.2318585708589135,"score_spread":0.2194877478946168,"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."}}