{"id":"W4385768408","doi":"10.1093/pnasnexus/pgad260","title":"Estimation of natural methane emissions from the largest oil sand deposits on earth","year":2023,"lang":"en","type":"article","venue":"PNAS Nexus","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Calgary","keywords":"Methane; Oil sands; Environmental science; Methane emissions; Natural gas; Fossil fuel; Monte Carlo method; Greenhouse gas; Atmospheric sciences; Petroleum engineering; Environmental engineering; Hydrology (agriculture); Geology; Waste management; Chemistry; Engineering; Geotechnical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000921399,0.00009987481,0.00009543028,0.000003078786,0.0001095438,0.000009789884,0.0001758488,0.00004456392,0.000326797],"category_scores_gemma":[0.00004716764,0.00006701259,0.00004363283,0.0002077622,0.0001140596,0.00007527459,0.0001395778,0.000119892,0.0004823589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003910599,"about_ca_system_score_gemma":0.000003569538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005213217,"about_ca_topic_score_gemma":0.00005450838,"domain_scores_codex":[0.9992148,0.00003970616,0.000127966,0.0001791305,0.000267764,0.0001706718],"domain_scores_gemma":[0.9995138,0.0001500063,0.00005821539,0.0002188797,0.000001000534,0.00005809191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00006505663,0.0001431089,0.05260819,0.000007852346,0.00004161788,0.00002148581,0.001332679,0.6292524,0.04651983,0.0001379588,0.001693751,0.268176],"study_design_scores_gemma":[0.0004916039,0.00008594996,0.7220181,0.00004098767,0.00004349624,0.000004752675,0.0002614407,0.2581701,0.01530919,0.0008419581,0.002496639,0.0002358244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942592,0.00005739509,0.00041543,0.0003607841,0.0001554361,0.00005339077,0.000007682399,0.00004397298,0.004646674],"genre_scores_gemma":[0.9931051,0.0000522728,0.003122956,0.0002260392,0.00002415723,0.000006915571,0.00003243342,0.00001226662,0.003417917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6694099,"threshold_uncertainty_score":0.6199909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00857063350862072,"score_gpt":0.2220725963434346,"score_spread":0.2135019628348139,"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."}}