{"id":"W3156112073","doi":"","title":"Improved understanding of methane emissions from oil and gas industries in western Canada using aircraft, satellite data, and GEOS-Chem model","year":2019,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Methane; Satellite; Methane emissions; Environmental science; Meteorology; Satellite tracking; Climatology; Remote sensing; Engineering; Geography; Aerospace engineering; Geology; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002528167,0.0001721761,0.0002266472,0.000007562963,0.0000527012,0.00002073423,0.00018316,0.0001091009,0.000007028314],"category_scores_gemma":[0.00004590561,0.0001695643,0.00001018682,0.000080819,0.0001457805,0.0002462703,0.0004453635,0.0002074158,0.00000110718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004110362,"about_ca_system_score_gemma":0.00006769662,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7829758,"about_ca_topic_score_gemma":0.5638342,"domain_scores_codex":[0.9987461,0.0000258779,0.0003138123,0.0004115331,0.0002215183,0.0002811898],"domain_scores_gemma":[0.9992572,0.0001384392,0.0001716849,0.0002905762,0.000001924153,0.0001401692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001649592,0.00001761483,0.7544117,0.00001875016,0.00001203073,0.000007926235,0.0003925349,0.2226776,0.01837721,0.000001019766,0.00000487993,0.004062192],"study_design_scores_gemma":[0.000803338,0.00002992751,0.1812855,0.0002635585,0.00004805379,0.00001102581,0.003790594,0.811765,0.001087365,0.0002448662,0.0002062729,0.0004644875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984065,0.0001661171,0.0002323416,0.000100706,0.0000394341,0.0000592979,0.00002579147,0.000009119879,0.0009606834],"genre_scores_gemma":[0.9897912,0.0002467305,0.009597936,0.00006611749,0.000007988174,8.34889e-7,0.00002002855,0.00001874558,0.0002504704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5890874,"threshold_uncertainty_score":0.6914633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011933123546586,"score_gpt":0.2275721861212373,"score_spread":0.1974528548857714,"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."}}