{"id":"W4205282243","doi":"10.1002/jwmg.22163","title":"Discriminating grey wolf kill sites using GPS clusters","year":2022,"lang":"en","type":"article","venue":"Journal of Wildlife Management","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry; Parks Canada; Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Parks Canada; Government of Ontario","keywords":"Odocoileus; Predation; Geography; Canis; Ungulate; Global Positioning System; Habitat; Cartography; National park; Cluster (spacecraft); Ecology; Biology; Computer science; Archaeology","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":[0.0007723572,0.0002654372,0.0002527946,0.002110473,0.0002308839,0.0006888296,0.0003213125,0.0002156192,0.0008698347],"category_scores_gemma":[0.00389815,0.000161083,0.0002250335,0.001583723,0.0002195251,0.0004233029,0.0004772086,0.0001684185,0.000281753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005653261,"about_ca_system_score_gemma":0.0004635999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05686875,"about_ca_topic_score_gemma":0.141403,"domain_scores_codex":[0.9995248,0.0001609514,0.00003718357,0.0001166619,0.0000956431,0.00006475511],"domain_scores_gemma":[0.9966875,0.001095046,0.001160785,0.0002299294,0.0006435226,0.0001832005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001058675,0.00001159391,0.9847772,0.00003082927,0.00007185535,0.00004293458,0.0002478883,0.002657598,0.00172571,0.00006287055,0.0002519428,0.01001367],"study_design_scores_gemma":[0.000004682685,0.00004521491,0.9886289,0.0000194379,0.00002334387,0.00008925096,0.0006964194,0.00954539,0.0004470266,0.0000974481,0.0003911553,0.00001177453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996053,0.00006821319,0.002113993,0.00002075559,0.000004040536,0.00002626058,0.0006161546,0.00002908315,0.001068542],"genre_scores_gemma":[0.9982741,0.00002838982,0.001100477,0.000005935028,0.000001993225,0.00000962486,0.0003767439,0.000003692851,0.0001990936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05686875,"threshold_uncertainty_score":0.1130754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02139274657447104,"score_gpt":0.2415770223425154,"score_spread":0.2201842757680443,"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."}}