{"id":"W4309030160","doi":"10.1016/j.rse.2022.113335","title":"Paddy rice methane emissions across Monsoon Asia","year":2022,"lang":"en","type":"article","venue":"Remote Sensing of Environment","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"College of Engineering, Michigan State University; Division of Chemical, Bioengineering, Environmental, and Transport Systems; HORIZON EUROPE Framework Programme; U.S. Geological Survey; Ministry of Agriculture, Forestry and Fisheries; European Commission; Chinese Academy of Agricultural Sciences; Rural Development Administration; Ministry of Environment; National Natural Science Foundation of China; National Research Foundation; Michigan State University; National Research Foundation of Korea; Gordon and Betty Moore Foundation; National Science Foundation","keywords":"Environmental science; Eddy covariance; Paddy field; Monsoon; Greenhouse gas; Methane; Atmospheric sciences; Climatology; Ecosystem; Agronomy; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0003710915,0.0006878052,0.0002397337,0.0003313216,0.000208582,0.0002872723,0.000449698,0.0001866649,0.000433541],"category_scores_gemma":[0.0003589421,0.000223089,0.0005056539,0.0004841436,0.0002264266,0.000346525,0.0003743284,0.0002267794,0.00009450045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006977853,"about_ca_system_score_gemma":0.0004033595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06097311,"about_ca_topic_score_gemma":0.04687267,"domain_scores_codex":[0.9999063,0.00001724097,0.000006343354,0.00004020074,0.00001258255,0.00001728387],"domain_scores_gemma":[0.9998784,0.00003147685,0.00001716254,0.00002059909,0.00003345638,0.00001880578],"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":[0.001081719,0.0002320667,0.4335591,0.0001783403,0.0005396177,0.0008594054,0.0003126184,0.4712773,0.05212066,0.0005836777,0.001281578,0.037974],"study_design_scores_gemma":[0.0001015873,0.0001819579,0.4771759,0.00001797578,0.0002071471,0.0001317261,0.0002086061,0.5070011,0.01348284,0.0003410324,0.001099816,0.0000502437],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981617,0.00004887688,0.0007044792,0.00002906667,0.000003292349,0.000005242376,0.0004734349,0.0001310292,0.0004428512],"genre_scores_gemma":[0.9986235,0.00003833234,0.0006178597,0.00001194076,0.000001356591,0.000005367648,0.0006001035,0.0000110478,0.00009057051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06097311,"threshold_uncertainty_score":0.1212364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007487834065876,"score_gpt":0.2276750739216699,"score_spread":0.2176001955810112,"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."}}