{"id":"W4306175371","doi":"10.5194/amt-15-5841-2022","title":"Comparing airborne algorithms for greenhouse gas flux measurements over the Alberta oil sands","year":2022,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Alberta Environment and Protected Areas; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; Alberta Innovates; Jet Propulsion Laboratory; University of Alberta; National Aeronautics and Space Administration; California Institute of Technology; Environment and Climate Change Canada; Alberta Environment and Parks","keywords":"Algorithm; Environmental science; Greenhouse gas; Extrapolation; Sampling (signal processing); Meteorology; Flux (metallurgy); Remote sensing; Computer science; Statistics; Mathematics; Physics; Geology; Detector","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001805324,0.0004779447,0.0003999942,0.000003104416,0.001227866,0.00006647236,0.001088493,0.00008562561,0.002858883],"category_scores_gemma":[0.00005710374,0.0003945088,0.0002486355,0.0004485816,0.0002852128,0.0002335086,0.0009337012,0.0003666008,0.00004506143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00203149,"about_ca_system_score_gemma":0.00003296539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00342347,"about_ca_topic_score_gemma":0.0005911636,"domain_scores_codex":[0.9956046,0.0002031701,0.0005760105,0.000766121,0.002079275,0.0007708187],"domain_scores_gemma":[0.9985905,0.00006462989,0.0003020597,0.0008477217,0.00002402325,0.0001710188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004461788,0.002098868,0.2624554,0.00008211794,0.0004973964,0.0000152775,0.001607414,0.06403789,0.0165555,0.0002577439,0.08105087,0.5708953],"study_design_scores_gemma":[0.0027755,0.00164494,0.05980565,0.00006860562,0.0004070685,0.00005934723,0.0008616205,0.1125542,0.004679161,0.001227791,0.8137724,0.002143657],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6857085,0.001182415,0.2329534,0.002092129,0.001485015,0.004812283,0.00002312451,0.001806839,0.06993626],"genre_scores_gemma":[0.8864251,0.00009404802,0.1034115,0.001706023,0.000128081,0.002515017,0.00002564168,0.0001621978,0.005532412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7327216,"threshold_uncertainty_score":0.9998507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03661253887126713,"score_gpt":0.2361830740016206,"score_spread":0.1995705351303535,"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."}}