{"id":"W3123104783","doi":"10.1002/lno.11660","title":"Seasonal patterns in greenhouse gas emissions from lakes and ponds in a High Arctic polygonal landscape","year":2021,"lang":"en","type":"article","venue":"Limnology and Oceanography","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University; Université Laval; Center for Northern Studies; Institut National de la Recherche Scientifique","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada; Natural Environment Research Council; Sight Research UK; W. Garfield Weston Foundation","keywords":"Thermokarst; Permafrost; Environmental science; Tundra; Arctic; Sink (geography); Greenhouse gas; Carbon dioxide; Carbon sink; Atmospheric sciences; Oceanography; Carbon cycle; Physical geography; Hydrology (agriculture); Ecology; Climate change; Geology; Ecosystem; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001532936,0.000150617,0.0001716327,0.0007408494,0.0004441991,0.0004993006,0.0001429425,0.0001499752,0.0004099745],"category_scores_gemma":[0.0002392898,0.0001123038,0.0001837453,0.0006530754,0.0003490407,0.0002216105,0.0003562732,0.000101444,0.00005840678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004634331,"about_ca_system_score_gemma":0.0001552291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01603633,"about_ca_topic_score_gemma":0.0395732,"domain_scores_codex":[0.9999118,0.00001339256,0.000005953632,0.0000279161,0.00001537306,0.00002561152],"domain_scores_gemma":[0.9997386,0.0000420602,0.0001032762,0.00001376761,0.00004719917,0.00005499209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002941402,0.00002426219,0.9797959,0.00002553423,0.0000818074,0.0002298368,0.0008774824,0.0007683518,0.01379975,0.00003062189,0.00005801013,0.004014242],"study_design_scores_gemma":[0.000001000077,0.00001551632,0.9987036,0.00000159946,0.000009853738,0.00004978764,0.0003586259,0.0004094217,0.0003285893,0.000007391751,0.0001121216,0.000002526316],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997994,0.00001885222,0.0000236878,0.000001748076,3.517268e-7,5.382916e-7,0.00006504689,0.000001477375,0.00008884328],"genre_scores_gemma":[0.9997501,0.00001626493,0.00006173794,0.000001182363,8.520469e-7,0.00000131451,0.0001032336,8.809687e-7,0.00006446873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01603633,"threshold_uncertainty_score":0.03188598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01424072968443174,"score_gpt":0.2115817841989245,"score_spread":0.1973410545144927,"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."}}