{"id":"W2585229638","doi":"10.1111/1365-2656.12645","title":"Many places called home: the adaptive value of seasonal adjustments in range fidelity","year":2017,"lang":"en","type":"article","venue":"Journal of Animal Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec à Montréal; Natural Sciences and Engineering Research Council of Canada; Université du Québec à Rimouski","funders":"Fonds de recherche du Québec – Nature et technologies; Canada Economic Development for Quebec Regions; Natural Sciences and Engineering Research Council of Canada; Canadian Wildlife Federation; Université du Québec à Rimouski","keywords":"Ungulate; Fidelity; Ecology; Range (aeronautics); Woodland caribou; Habitat; Biology; Boreal; Home range; Reproductive success; Adaptive value; Predation; Geography; Demography; Population","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003871837,0.0001293487,0.0002253358,0.0003773142,0.0004095415,0.0007842223,0.0003536997,0.000274551,0.0009630003],"category_scores_gemma":[0.002079868,0.0001447302,0.000157415,0.0003151766,0.0006007634,0.0003392171,0.0004395158,0.0003996685,0.00007407546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006767181,"about_ca_system_score_gemma":0.000340597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06337123,"about_ca_topic_score_gemma":0.1851976,"domain_scores_codex":[0.9997939,0.00004224774,0.000007409525,0.00006880117,0.00003311181,0.00005444064],"domain_scores_gemma":[0.9986072,0.0003216281,0.000469571,0.0001802593,0.0001397008,0.0002815633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000747491,0.00003652338,0.9848852,0.00001114472,0.00008177701,0.00008441571,0.0007441367,0.0005621905,0.004989491,0.0001380072,0.00012572,0.008266704],"study_design_scores_gemma":[3.718069e-7,0.00001207858,0.9994171,0.000001346545,0.000004332513,0.00003081509,0.0001759183,0.0002085188,0.00004509358,0.00003374192,0.0000682742,0.000002413473],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991394,0.00008857,0.0001844249,0.00003504774,0.000001619341,0.000001365082,0.00005565599,0.000006230736,0.0004875526],"genre_scores_gemma":[0.9996704,0.00002442845,0.0001321982,0.00001169168,0.000001467823,0.000001105725,0.00004863253,0.000001985207,0.0001081727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06337123,"threshold_uncertainty_score":0.1260048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857774889837813,"score_gpt":0.2590940873708164,"score_spread":0.2405163384724382,"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."}}