{"id":"W4362588053","doi":"10.1007/s10021-023-00835-3","title":"Integrating Beaver Ponds into the Carbon Emission Budget of Boreal Aquatic Networks: A Case Study at the Watershed Scale","year":2023,"lang":"en","type":"article","venue":"Ecosystems","topic":"Ecology and biodiversity studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Beaver; Environmental science; Biome; Boreal; Ecosystem; Ecology; Watershed; Greenhouse gas; Population; Hydrology (agriculture); Biology","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":[0.0006154258,0.0002616444,0.000195538,0.0005519063,0.001363837,0.00150741,0.0005675702,0.0005486324,0.001112992],"category_scores_gemma":[0.001705162,0.0001528241,0.0002756371,0.001164936,0.0007936694,0.001081629,0.0008698832,0.0003666729,0.00005301478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001985654,"about_ca_system_score_gemma":0.001342042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08472413,"about_ca_topic_score_gemma":0.231492,"domain_scores_codex":[0.9996822,0.0001095493,0.00001318817,0.00006330672,0.00005107035,0.00008062187],"domain_scores_gemma":[0.9992068,0.0003131803,0.0001202512,0.00006446025,0.0001346509,0.0001605946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004262166,0.0008862517,0.65381,0.0001160189,0.0002010654,0.006974158,0.00265917,0.2331046,0.01218086,0.01043688,0.001088221,0.07811666],"study_design_scores_gemma":[0.00007129574,0.0007830679,0.4941071,0.00008801926,0.0002484281,0.0017393,0.01248819,0.4680141,0.005574736,0.01011791,0.006679987,0.00008793544],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954504,0.00003408286,0.001688921,0.00004973301,0.000002531677,0.00003507731,0.0000607153,0.00002256877,0.002655998],"genre_scores_gemma":[0.9973428,0.00002948842,0.002154845,0.000006457786,0.000001129416,0.000008138408,0.00003131641,0.000004544295,0.0004213767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08472413,"threshold_uncertainty_score":0.168462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0103314216924987,"score_gpt":0.2223637895269096,"score_spread":0.2120323678344109,"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."}}