{"id":"W2950888176","doi":"10.5194/amt-12-6771-2019","title":"A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor","year":2019,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":150,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Remote sensing; Differential optical absorption spectroscopy; Environmental science; Radiance; Satellite; Imaging spectrometer; Troposphere; SCIAMACHY; Nadir; Trace gas; Spectrometer; Greenhouse gas; Hyperspectral imaging; Algorithm; Meteorology; Computer science; Absorption (acoustics); Physics; Geology; Optics","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":[0.0007826064,0.0007848593,0.0004524267,0.0007415585,0.0005393059,0.000726742,0.001202756,0.0007856832,0.002058191],"category_scores_gemma":[0.001413305,0.0002850172,0.0005728454,0.0006522975,0.000302096,0.0006813373,0.001087939,0.0007613011,0.001540917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005380015,"about_ca_system_score_gemma":0.001679108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005484531,"about_ca_topic_score_gemma":0.005503662,"domain_scores_codex":[0.9996315,0.00004334817,0.00003203184,0.0001105616,0.0001344489,0.00004807242],"domain_scores_gemma":[0.9997082,0.00004534748,0.00003718061,0.00003682135,0.0001524463,0.00001994067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003672225,0.0002115243,0.007197648,0.000109044,0.0001836619,0.0001509752,0.0001391426,0.1924878,0.05775015,0.007183493,0.008494852,0.7257245],"study_design_scores_gemma":[0.00004669019,0.00006014369,0.001105059,0.000005853903,0.00001497595,0.00005755185,0.00002962349,0.9858727,0.007855996,0.001794673,0.003142132,0.0000144447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0198886,0.00009580113,0.9763906,0.00008717403,0.00006990149,0.0001471688,0.0001195416,0.00199999,0.001201223],"genre_scores_gemma":[0.1038244,0.00006889606,0.891794,0.00009630257,0.00005013552,0.0004073481,0.001149168,0.0001236979,0.002486054],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005484531,"threshold_uncertainty_score":0.01090521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008404482313905816,"score_gpt":0.2017753567273454,"score_spread":0.1933708744134396,"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."}}