{"id":"W4416285068","doi":"10.1111/1365-2435.70197","title":"Integrating predator energetic balance, risk‐taking behaviour and microhabitat in functional response to untangle indirect interactions in a multispecies vertebrate community","year":2025,"lang":"en","type":"article","venue":"Functional Ecology","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Center for Northern Studies; Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada; Kenneth M. Molson Foundation; Polar Knowledge Canada; Canada Foundation for Innovation; Arctic Goose Joint Venture; Université du Québec à Rimouski; Environment Canada; Canada Research Chairs; ArcticNet; Fonds de recherche du Québec – Nature et technologies; Université Laval","keywords":"Predation; Tundra; Foraging; Predator; Functional response; Vertebrate; Nest (protein structural motif); Arctic; Optimal foraging theory","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":[0.000838239,0.0005590239,0.0004378932,0.0004639229,0.0003503878,0.00084851,0.0007979939,0.001013152,0.001868765],"category_scores_gemma":[0.001482919,0.0004823906,0.001030151,0.0001881245,0.0004269429,0.0008038607,0.0005764258,0.0005066717,0.0002381306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001164053,"about_ca_system_score_gemma":0.0005265483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01482225,"about_ca_topic_score_gemma":0.01284481,"domain_scores_codex":[0.9998077,0.00006790904,0.00001050188,0.00006075832,0.00001508493,0.00003806937],"domain_scores_gemma":[0.9993262,0.00030827,0.0001359964,0.00004663289,0.00007012199,0.0001127301],"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":[0.0001370611,0.0001493515,0.1059531,0.00005799759,0.0002741581,0.0001582038,0.0001101248,0.8770775,0.01249746,0.0009507074,0.0001286324,0.002505826],"study_design_scores_gemma":[0.000007414978,0.00007320841,0.02882604,0.000005633696,0.00003260895,0.00003381826,0.00004492994,0.9699392,0.0004041542,0.0005293716,0.00008776216,0.00001584543],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928606,0.0000348086,0.006404483,0.00006774149,0.000004323244,0.000008377631,0.00009981656,0.00003671395,0.0004830802],"genre_scores_gemma":[0.9985524,0.00001158341,0.001151427,0.00001750592,0.000001573637,0.00001008926,0.00004513395,0.000007560832,0.0002027476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01482225,"threshold_uncertainty_score":0.02947193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01945355254490129,"score_gpt":0.2684033707632204,"score_spread":0.248949818218319,"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."}}