{"id":"W4386348294","doi":"10.1088/1748-9326/acf603","title":"Assessing the potential benefits of methane oxidation technologies using a concentration-based framework","year":2023,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"United Nations Environment Programme; Natural Sciences and Engineering Research Council of Canada; Stanford Woods Institute for the Environment; Gordon and Betty Moore Foundation","keywords":"Methane; Oxidizing agent; Environmental science; Radiative forcing; Greenhouse gas; Anaerobic oxidation of methane; Atmospheric methane; Environmental chemistry; Carbon dioxide; Global warming; Atmospheric sciences; Chemistry; Climate change; Ecology; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009817311,0.0001793827,0.0001550374,0.00003278138,0.0003723238,0.00006816039,0.0005155012,0.0001267389,0.0004948024],"category_scores_gemma":[0.0001119103,0.000145194,0.00008606102,0.0006814327,0.00186303,0.0003744971,0.0005046473,0.0004506433,0.0002188954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005501513,"about_ca_system_score_gemma":0.00001208515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001212306,"about_ca_topic_score_gemma":0.000001825412,"domain_scores_codex":[0.9971529,0.0002463117,0.0002878489,0.0004117876,0.001290689,0.000610434],"domain_scores_gemma":[0.9990179,0.0003336585,0.000124414,0.0004554428,0.000002006291,0.00006657907],"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":[0.00001233415,0.00006131345,0.04783724,0.000005460065,0.00001360992,0.00001317964,0.000129739,0.5090969,0.4324916,0.00002395697,0.00009846587,0.01021615],"study_design_scores_gemma":[0.0006819174,0.0001495858,0.5723301,0.00009209424,0.00004868676,0.00001560734,0.007179984,0.3419862,0.07518245,0.001264486,0.0005231349,0.0005457398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9753467,0.00007668674,0.02184608,0.00210911,0.00008294777,0.0003839466,0.000005597085,0.00008650593,0.00006241754],"genre_scores_gemma":[0.9870488,0.0001065523,0.01246996,0.0002149408,0.00002950874,0.00003418894,0.00002464648,0.00003093377,0.00004047007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5244929,"threshold_uncertainty_score":0.6864413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0376552924642664,"score_gpt":0.3205792425295173,"score_spread":0.2829239500652509,"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."}}