{"id":"W2133597100","doi":"10.1644/1545-1542(2005)086[0736:mdsmam]2.0.co;2","title":"MULE DEER SEASONAL MOVEMENTS AND MULTISCALE RESOURCE SELECTION USING GLOBAL POSITIONING SYSTEM RADIOTELEMETRY","year":2005,"lang":"en","type":"article","venue":"Journal of Mammalogy","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Insight Electronics (Canada)","funders":"","keywords":"Odocoileus; Ungulate; Home range; Habitat; Range (aeronautics); Geography; Population; Ecology; Snow; Selection (genetic algorithm); Scale (ratio); Environmental science; Physical geography; Biology; Cartography; Meteorology; Demography; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002720241,0.000130701,0.0001328785,0.0006321703,0.0001963681,0.0003792359,0.0001435556,0.0001315756,0.0006533054],"category_scores_gemma":[0.001229369,0.0001205608,0.00007888165,0.000478174,0.0002345612,0.0002612073,0.0002101815,0.0001239621,0.00008220291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003669919,"about_ca_system_score_gemma":0.0001786353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07921277,"about_ca_topic_score_gemma":0.2725566,"domain_scores_codex":[0.9998673,0.00003523221,0.000006723114,0.00004271844,0.00002074387,0.00002732447],"domain_scores_gemma":[0.9995033,0.0001169565,0.0001980542,0.00005061478,0.00006428026,0.00006695528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003804433,0.0000118679,0.9926131,0.000004635539,0.00002343627,0.00003010737,0.0001744972,0.0002081522,0.0009568277,0.00001271,0.00007749669,0.00584906],"study_design_scores_gemma":[8.905462e-7,0.000008278127,0.9996054,0.000001294134,0.000003165781,0.00001593768,0.00004667114,0.0002325775,0.00002924773,0.00000855118,0.00004692066,0.000001096347],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994813,0.00004362555,0.0001173659,0.000009722912,4.417078e-7,0.000003034397,0.0001167132,0.000003923548,0.000223904],"genre_scores_gemma":[0.9994639,0.00003169981,0.0002064662,0.00000615843,0.000001105629,0.000004890889,0.0001478022,0.000001203379,0.0001368986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07921277,"threshold_uncertainty_score":0.1575034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006848963734584464,"score_gpt":0.2240493173127936,"score_spread":0.2172003535782091,"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."}}