{"id":"W4405691895","doi":"10.1002/lno.12767","title":"A simple approach to quantifying whole‐lake methane ebullition and sedimentary methane production, and its application to the Canadian Lake Pulse dataset","year":2024,"lang":"en","type":"article","venue":"Limnology and Oceanography","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Groupe de recherche interuniversitaire en limnologie","keywords":"Flux (metallurgy); Sediment; Atmosphere (unit); Environmental science; Methane; Sediment–water interface; Hydrology (agriculture); Sedimentary rock; Atmospheric sciences; Geology; Chemistry; Geomorphology; Geochemistry; Meteorology; Physics","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":[0.0007640539,0.000855198,0.0003407903,0.002715362,0.001349545,0.0009618886,0.001205593,0.0004834212,0.001295221],"category_scores_gemma":[0.001597588,0.0002937644,0.0006649535,0.003724843,0.0003551389,0.0002948416,0.0009327907,0.0004285794,0.0004185387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003663312,"about_ca_system_score_gemma":0.007427571,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8765278,"about_ca_topic_score_gemma":0.9526281,"domain_scores_codex":[0.9994451,0.0000394271,0.00002967835,0.0001645039,0.0002215081,0.00009971057],"domain_scores_gemma":[0.999398,0.00005292396,0.00005474065,0.00007139194,0.0003833824,0.00003965662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005341992,0.0002798496,0.6577409,0.0007341874,0.001091645,0.00041696,0.0008048516,0.06669959,0.05889336,0.002274132,0.04445213,0.1660781],"study_design_scores_gemma":[0.0000782614,0.00004368416,0.88376,0.0000375976,0.0000835088,0.00006635298,0.0003023437,0.08031697,0.007945651,0.0003953929,0.02687249,0.00009776025],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7480444,0.0007641378,0.02719944,0.0003048685,0.00003944345,0.0005202846,0.2124884,0.003424352,0.00721472],"genre_scores_gemma":[0.738936,0.0003470175,0.07255683,0.0001403585,0.00002713769,0.000624902,0.1831582,0.000253818,0.003955706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1234722,"threshold_uncertainty_score":0.2483985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01349310158588644,"score_gpt":0.2333920517800778,"score_spread":0.2198989501941913,"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."}}