{"id":"W3126549621","doi":"10.5194/amt-14-945-2021","title":"Quantifying fugitive gas emissions from an oil sands tailings pond with open-path Fourier transform infrared measurements","year":2021,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Suncor Energy (Canada); Alberta Environment and Protected Areas; Environment and Climate Change Canada","funders":"Albert Einstein College of Medicine, Yeshiva University; Natural Resources Canada; Environment and Climate Change Canada; Suncor Energy Incorporated","keywords":"Eddy covariance; Fugitive emissions; Flux (metallurgy); Environmental science; Methane; Oil sands; Atmospheric sciences; Dispersion (optics); Atmosphere (unit); Tailings; Greenhouse gas; Environmental chemistry; Soil science; Chemistry; Meteorology; Geology; Materials science; Physics; Ecosystem","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":[0.0002044157,0.0002493007,0.0001505844,0.0005485757,0.0003767232,0.0004622983,0.0003109628,0.0002363827,0.0004650355],"category_scores_gemma":[0.0002362027,0.00009665808,0.0001700327,0.0005133516,0.0002838528,0.000359055,0.0002849018,0.0001908334,0.00009903697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001088519,"about_ca_system_score_gemma":0.0007379463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07802836,"about_ca_topic_score_gemma":0.231112,"domain_scores_codex":[0.9997781,0.00001250897,0.000004727877,0.00004207887,0.000135664,0.0000269043],"domain_scores_gemma":[0.9999061,0.00001613294,0.00002140788,0.000004865135,0.00004147197,0.000009963301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003206868,0.0001623889,0.2585328,0.0001338987,0.00005148448,0.0001675904,0.0002870062,0.00551324,0.6778916,0.0002356911,0.000281929,0.05642185],"study_design_scores_gemma":[0.0000240329,0.0002744982,0.6709015,0.00002556557,0.00006569832,0.0001401806,0.0007034,0.04757802,0.2778598,0.0003096066,0.00207997,0.0000377736],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949362,0.00004673915,0.003724087,0.00001364037,0.000002123968,0.00001580498,0.0001702797,0.00006091383,0.001030125],"genre_scores_gemma":[0.9917977,0.0000801436,0.007129571,0.00001367564,0.000001684408,0.00001271066,0.0002112784,0.000008576153,0.0007446626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07802836,"threshold_uncertainty_score":0.1551483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0404463280669434,"score_gpt":0.2638911366093331,"score_spread":0.2234448085423897,"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."}}