{"id":"W654488244","doi":"10.5962/p.364028","title":"Assessing Southern Flying Squirrel, Glaucomys volans, habitat selection with kernel home range estimation and GIS","year":2000,"lang":"en","type":"article","venue":"The Canadian Field-Naturalist","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Forest Service","keywords":"Home range; Range (aeronautics); Geography; Selection (genetic algorithm); Habitat; Mark and recapture; Ecology; Biology; Engineering; Computer science; Artificial intelligence; Demography; Aerospace engineering; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007560628,0.0001865535,0.0001303725,0.001053233,0.0001812447,0.0002942204,0.0001723454,0.00009279689,0.0004893666],"category_scores_gemma":[0.001630167,0.0001506237,0.0001220779,0.0005460404,0.000177482,0.0004477747,0.0002678373,0.00007851826,0.0001032021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002537985,"about_ca_system_score_gemma":0.0001808825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01995748,"about_ca_topic_score_gemma":0.07241224,"domain_scores_codex":[0.9997622,0.0001212203,0.00001659331,0.00003549032,0.00004877114,0.00001575057],"domain_scores_gemma":[0.9993597,0.0002377689,0.0001945329,0.00005677153,0.0000978394,0.00005342161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001453061,0.00005175458,0.9646686,0.00002871501,0.00007029056,0.00006505832,0.0002931121,0.002986567,0.00351118,0.0001158185,0.0001679534,0.02789575],"study_design_scores_gemma":[0.000007437632,0.0001359773,0.9816576,0.000005608846,0.00003252995,0.0001819936,0.0004045904,0.01614271,0.001058149,0.0001536072,0.000213145,0.000006699913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996497,0.00003308878,0.0030729,0.000008491801,3.318519e-7,0.00000631814,0.00008311737,0.0000360112,0.0002627198],"genre_scores_gemma":[0.9930033,0.00002650187,0.006672929,0.000002892366,9.952812e-7,0.000008701292,0.0001588939,0.000003324531,0.0001224707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01995748,"threshold_uncertainty_score":0.03968263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01281996233915296,"score_gpt":0.2354898052782653,"score_spread":0.2226698429391124,"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."}}