{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001432959,0.000116768,0.0001019477,0.00002374803,0.001099555,0.0001153229,0.000115955,0.00009908053,0.002455957],"category_scores_gemma":[0.00001605073,0.00008016678,0.00002038677,0.0001300631,0.0002047743,0.000255978,0.00001982542,0.0002398921,0.0003105318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001953032,"about_ca_system_score_gemma":0.0000248222,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1418008,"about_ca_topic_score_gemma":0.8114009,"domain_scores_codex":[0.9992922,0.00004874446,0.00009354104,0.0002051441,0.0001046665,0.0002557155],"domain_scores_gemma":[0.9997023,0.00005160333,0.00003440294,0.0001062073,0.000007693677,0.00009776046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004620087,0.00001131393,0.9304488,0.000008341674,0.00002086414,0.00002855759,0.002569054,0.00009494743,0.0001511359,0.00005912483,0.004247427,0.06231423],"study_design_scores_gemma":[0.0002252538,0.00005744876,0.9945168,0.00001798472,0.00005423733,0.00006678563,0.0005853751,0.001698402,0.0000187788,0.0001670329,0.002392446,0.000199476],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899372,0.00006322136,0.0000293144,0.004301152,0.00005578013,0.0001357518,0.000006528869,0.0000276995,0.005443347],"genre_scores_gemma":[0.9963265,0.000007901918,0.00030012,0.0009828387,0.0000295414,0.00001149799,0.000006679291,0.000009202478,0.002325737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6696001,"threshold_uncertainty_score":0.9984559,"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."}}