{"id":"W2144752794","doi":"10.1111/1365-2656.12115","title":"Increasing density leads to generalization in both coarse‐grained habitat selection and fine‐grained resource selection in a large mammal","year":2013,"lang":"en","type":"article","venue":"Journal of Animal Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Community College; Université de Sherbrooke; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Habitat; Ecology; Selection (genetic algorithm); Population; Vegetation (pathology); Population density; Competition (biology); Geography; Biology","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":[0.0002568609,0.000107117,0.0001575268,0.0002641502,0.0002437022,0.0003207512,0.0001546132,0.0001562545,0.001142521],"category_scores_gemma":[0.0009653171,0.0001980584,0.0001856572,0.0001116187,0.0005172135,0.0001683111,0.0004698043,0.0003615626,0.00008878284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005828222,"about_ca_system_score_gemma":0.0002330061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02272806,"about_ca_topic_score_gemma":0.05958036,"domain_scores_codex":[0.9998721,0.00002997202,0.000008150066,0.00003836592,0.00002219535,0.00002925129],"domain_scores_gemma":[0.9995093,0.0001484457,0.0001346129,0.00007407927,0.00004043619,0.00009308288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005092747,0.0002871043,0.782699,0.00005453832,0.00009772135,0.0003909697,0.001079689,0.00206006,0.1943684,0.000541964,0.0004117553,0.01749943],"study_design_scores_gemma":[0.00000302871,0.00006139019,0.9978536,0.000002564926,0.000006601269,0.00005451743,0.0001147823,0.0009744635,0.0007498621,0.0000902349,0.00008503917,0.0000038989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996227,0.00001605797,0.00008712213,0.00001130162,6.798427e-7,0.000001957829,0.00001196971,0.000004084498,0.0002440306],"genre_scores_gemma":[0.9996641,0.00001685161,0.0001135066,0.00002153675,9.134478e-7,0.000004266939,0.00002887435,0.000001812591,0.0001481445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02272806,"threshold_uncertainty_score":0.04519153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007332542039660868,"score_gpt":0.2187575270562321,"score_spread":0.2114249850165712,"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."}}