{"id":"W2144660547","doi":"10.1111/j.1541-0064.2008.00207.x","title":"Snow‐tracking and GIS: using multiple species‐environment models to determine optimal wildlife crossing sites and evaluate highway mitigation plans on the Trans‐Canada Highway","year":2008,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Park Service; Parks Canada; University of Calgary","keywords":"Terrain; Geography; Wildlife; Vegetation (pathology); Elevation (ballistics); Transect; Physical geography; Habitat; Normalized Difference Vegetation Index; Environmental science; Geographic information system; Ecology; Remote sensing; Cartography; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0002208587,0.0004217683,0.0002901885,0.0006482326,0.002589441,0.0002597081,0.0002681442,0.0001045194,0.0001650542],"category_scores_gemma":[0.00006561857,0.000377474,0.00009574153,0.001141216,0.001614465,0.0005625988,0.00006332625,0.0002263281,0.000003287421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004077913,"about_ca_system_score_gemma":0.0001499112,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9176859,"about_ca_topic_score_gemma":0.9974192,"domain_scores_codex":[0.9975516,0.00009396259,0.0004097466,0.0006849041,0.0004142866,0.0008455673],"domain_scores_gemma":[0.9983423,0.0002535739,0.0001304311,0.0004026358,0.000036372,0.0008347259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001039802,0.00005704616,0.9066841,0.00003334879,0.0002129182,0.0001703229,0.008654681,0.05206304,0.003998565,0.000534029,0.01773764,0.009750345],"study_design_scores_gemma":[0.0006019425,0.0002319687,0.9050312,0.0001671588,0.0001043551,0.0001978778,0.00591477,0.03373901,0.0004491905,0.0001701433,0.05230153,0.001090846],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940248,0.0001273749,0.0001008407,0.004305344,0.000201133,0.0005804369,0.0002776913,0.00003774431,0.0003446653],"genre_scores_gemma":[0.9958439,0.0002986049,0.0006565753,0.002832509,0.00007107022,0.00007098297,0.0000428789,0.00004228665,0.0001412006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07973327,"threshold_uncertainty_score":0.9998677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02858984387358521,"score_gpt":0.1979971191408976,"score_spread":0.1694072752673124,"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."}}