{"id":"W4200293255","doi":"10.1016/j.scitotenv.2021.152459","title":"Modeling the spatial and temporal variability in surface water CO2 and CH4 concentrations in a newly created complex of boreal hydroelectric reservoirs","year":2021,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Environmental science; Greenhouse gas; Methane; Spatial variability; Hydrology (agriculture); Boreal; Hydroelectricity; Surface water; Flooding (psychology); Flood myth; Carbon dioxide; Atmospheric sciences; Ecology; Geology; Environmental engineering; Oceanography; Geography","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":[0.0003101107,0.0004596618,0.0003472316,0.0003467385,0.0004251417,0.0008825694,0.00112467,0.0009995007,0.0005032531],"category_scores_gemma":[0.0009479374,0.0003650796,0.0007857408,0.0004079958,0.0005752997,0.0005103484,0.0006336772,0.0005059193,0.00005337322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001291627,"about_ca_system_score_gemma":0.001044774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1243265,"about_ca_topic_score_gemma":0.08036403,"domain_scores_codex":[0.9998698,0.00002975321,0.000008784561,0.00005010276,0.00001131976,0.00003012912],"domain_scores_gemma":[0.9995814,0.0001889343,0.00009552909,0.00003564953,0.00005057734,0.00004794867],"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":[0.00006659445,0.00008001233,0.02559149,0.00001663289,0.00005577957,0.0001303012,0.00004837375,0.9703254,0.00172412,0.0005647884,0.0001373511,0.001259282],"study_design_scores_gemma":[0.00001171387,0.00001356658,0.005453648,0.000001689546,0.0000102484,0.00001112533,0.00002525911,0.9940735,0.0001767071,0.0001106461,0.0001054481,0.000006443945],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950969,0.00005187446,0.0035463,0.0001175773,0.000007547369,0.00001482584,0.0003678822,0.00007672034,0.000720423],"genre_scores_gemma":[0.9959617,0.00003163989,0.003410628,0.0000112998,0.000006116634,0.00002278406,0.0002497927,0.00001233193,0.0002937512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1243265,"threshold_uncertainty_score":0.2472056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030784613152224,"score_gpt":0.2016043532667545,"score_spread":0.1912965071352323,"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."}}