{"id":"W2081072530","doi":"10.5194/acp-15-3893-2015","title":"Spatial and temporal variation in CO over Alberta using measurements from satellites, aircraft, and ground stations","year":2015,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas; University of Alberta","funders":"Canadian Space Agency; Mitacs; National Aeronautics and Space Administration; Goddard Space Flight Center; National Oceanic and Atmospheric Administration; National Center for Atmospheric Research; National Science Foundation","keywords":"Environmental science; Troposphere; Atmospheric sciences; Ozone Monitoring Instrument; Trace gas; Moderate-resolution imaging spectroradiometer; Spatial variability; Satellite; Atmosphere (unit); Seasonality; Meteorology; Climatology; Geology; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001768879,0.0002494232,0.0001280939,0.00115616,0.0005610909,0.0006667649,0.000371858,0.0001737496,0.0005376252],"category_scores_gemma":[0.0003222924,0.0001248055,0.0001533651,0.002408218,0.0002405881,0.0001580307,0.0003066425,0.0001682207,0.0001237013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005000832,"about_ca_system_score_gemma":0.003271768,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9611845,"about_ca_topic_score_gemma":0.9813446,"domain_scores_codex":[0.9998301,0.000008066621,0.000004707957,0.0000345067,0.00008583014,0.00003685071],"domain_scores_gemma":[0.9996494,0.0000254988,0.00005407648,0.00001291233,0.0002102662,0.00004784833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001872957,0.00004851555,0.9717359,0.00003323732,0.00007079837,0.0001929785,0.0003888598,0.003882081,0.005992377,0.0001414602,0.001273407,0.01605303],"study_design_scores_gemma":[0.00000481356,0.000008949,0.9944417,0.000008923586,0.00001664896,0.0000278589,0.0003483802,0.003281081,0.0005102662,0.00001581878,0.001328647,0.000006884732],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934969,0.0002780952,0.0003325042,0.00004525463,0.000007430284,0.00001277664,0.002998201,0.00003387201,0.002794888],"genre_scores_gemma":[0.9940017,0.0002215937,0.000760571,0.00001727325,0.000005441857,0.000006998667,0.003492796,0.000006439124,0.00148721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0388155,"threshold_uncertainty_score":0.0780881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751683279901924,"score_gpt":0.2236088002491193,"score_spread":0.2060919674501001,"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."}}