{"id":"W3122264597","doi":"10.1016/j.biocon.2021.108968","title":"COVID19-induced reduction in human disturbance enhances fattening of an overabundant goose species","year":2021,"lang":"en","type":"article","venue":"Biological Conservation","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Rimouski; Environment and Climate Change Canada; Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; ArcticNet; Networks of Centres of Excellence of Canada; Canada First Research Excellence Fund; Eastern Bird Banding Association","keywords":"Disturbance (geology); Goose; Foraging; Waterfowl; Ecology; Habitat; Wildlife; Population; Trophic level; Anatidae; Geography; Ecosystem; Predation; Fishery; Biology; Environmental science; Demography","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":[0.0001290832,0.0002952954,0.0004360275,0.0002733071,0.0003752793,0.0004102253,0.0002778773,0.0003937651,0.00526612],"category_scores_gemma":[0.0002028055,0.0001807011,0.0002915368,0.0001941106,0.0003709294,0.0001483972,0.0004824869,0.0008521882,0.0003810401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000356813,"about_ca_system_score_gemma":0.000373863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002666257,"about_ca_topic_score_gemma":0.006594897,"domain_scores_codex":[0.9998206,0.00001564676,0.00001137819,0.00004681205,0.00002352825,0.00008214462],"domain_scores_gemma":[0.9998007,0.00001494963,0.00005004157,0.00001992356,0.00001635885,0.00009799831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002816205,0.0005453155,0.003301901,0.0001390558,0.00004853243,0.0002126629,0.00005621652,0.0001174329,0.9869301,0.0001136662,0.0004308018,0.005287953],"study_design_scores_gemma":[0.0004540185,0.00890642,0.3268396,0.0000662251,0.0003129459,0.00109034,0.001003369,0.00183345,0.6433601,0.0002211704,0.01584593,0.00006645963],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976738,0.0003434382,0.000260377,0.00008993602,0.00009277151,0.00001951684,0.0004932705,0.0000444806,0.0009823972],"genre_scores_gemma":[0.9928308,0.0004409835,0.000529257,0.0001807352,0.0000268377,0.00007656242,0.001447185,0.00003051906,0.004437081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00526612,"threshold_uncertainty_score":0.01761699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06198314489929072,"score_gpt":0.287463975736244,"score_spread":0.2254808308369533,"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."}}