{"id":"W4213293468","doi":"10.1002/ece3.8589","title":"Beyond the encounter: Predicting multi‐predator risk to elk (<i>Cervus canadensis</i>) in summer using predator scats","year":2022,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; Natural Sciences and Engineering Research Council of Canada; Parks Canada; Rocky Mountain Elk Foundation; International Association for Bear Research and Management; TD Friends of the Environment Foundation; Alberta Environment and Parks; University of Montana; Alberta Conservation Association; National Science Foundation","keywords":"Predation; Predator; Ursus; Ecology; Biology; Wildlife; Apex predator; Canis; Cervus; Geography; Population; Demography","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":[0.0004076951,0.0003355502,0.0001751016,0.0008329052,0.0003204687,0.0005634127,0.0003115955,0.0002554142,0.000526251],"category_scores_gemma":[0.0009932271,0.000156236,0.0002278814,0.0003094498,0.0001727164,0.0002149275,0.0003089778,0.0001505602,0.0001517308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093931,"about_ca_system_score_gemma":0.000441651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1416392,"about_ca_topic_score_gemma":0.3241253,"domain_scores_codex":[0.9998995,0.00001493642,0.000006203316,0.00003298104,0.00002796586,0.00001836995],"domain_scores_gemma":[0.9993394,0.000178318,0.0002357051,0.00002959861,0.0001138848,0.0001029622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003693754,0.00001184597,0.9942929,0.000006043018,0.00002651961,0.00001550429,0.00005210702,0.003410754,0.0006262244,0.00001387737,0.0000469333,0.001460317],"study_design_scores_gemma":[0.000002489612,0.00003868855,0.9688587,0.000008258316,0.00001978643,0.00004406542,0.0002581162,0.03022582,0.0003788906,0.000049751,0.0001097757,0.000005804714],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992045,0.00003077949,0.0003027987,0.00000730261,7.765227e-7,0.000003569474,0.000185882,0.00001623709,0.0002480965],"genre_scores_gemma":[0.9989858,0.00002139179,0.0006146557,0.000004376004,9.94314e-7,0.000002945238,0.0002671064,0.000002384421,0.0001003438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1416392,"threshold_uncertainty_score":0.2816296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01106018877994065,"score_gpt":0.223484187329425,"score_spread":0.2124239985494844,"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."}}