{"id":"W2081090308","doi":"10.1016/j.rse.2012.05.008","title":"Biases in long-term NO2 averages inferred from satellite observations due to cloud selection criteria","year":2012,"lang":"en","type":"article","venue":"Remote Sensing of Environment","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Ozone Monitoring Instrument; Troposphere; Satellite; Trace gas; Atmospheric sciences; Meteorology; Cloud fraction; Cloud cover; Cloud computing; Geography; Physics","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":[0.001524382,0.0002784464,0.0002818491,0.0006326377,0.0003826213,0.0007746034,0.000386727,0.0004043167,0.0004815198],"category_scores_gemma":[0.005406177,0.0002109462,0.0003435696,0.0008242237,0.0002273052,0.0007477967,0.0003435827,0.0002164272,0.0001165259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006968487,"about_ca_system_score_gemma":0.0005433565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01572119,"about_ca_topic_score_gemma":0.02644518,"domain_scores_codex":[0.9994987,0.0000924802,0.00006794123,0.0001280406,0.0001016625,0.0001112264],"domain_scores_gemma":[0.9967361,0.001749403,0.000456307,0.0003238628,0.0005912207,0.000143112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001051723,0.0001016474,0.8921982,0.0001497337,0.0005111737,0.0001801262,0.0001838706,0.03240694,0.04736499,0.0008165163,0.0009228158,0.02411226],"study_design_scores_gemma":[0.00004924068,0.00004364514,0.9202251,0.00002389755,0.0001865791,0.00007950663,0.00006532918,0.06517708,0.01270138,0.0007606487,0.0006582772,0.00002932745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961515,0.0002501111,0.002220485,0.00005257084,0.00004195183,0.000006299383,0.0005127848,0.00005298836,0.0007113719],"genre_scores_gemma":[0.9982936,0.00005874303,0.0008036114,0.00002422355,0.00002631331,0.000003026389,0.0006549621,0.00001880986,0.0001168016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01572119,"threshold_uncertainty_score":0.03125942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03735090834614484,"score_gpt":0.2415405524018301,"score_spread":0.2041896440556852,"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."}}