{"id":"W2993709676","doi":"10.1007/s10344-019-1333-z","title":"Simulating animal movements to predict wildlife-vehicle collisions: illustrating an application of the novel R package SiMRiv","year":2019,"lang":"en","type":"article","venue":"European Journal of Wildlife Research","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Canada Excellence Research Chairs, Government of Canada","keywords":"Wildlife; Lutra; Movement (music); Landscape connectivity; Computer science; Otter; Geography; Ecology; Environmental resource management; Environmental science; Biological dispersal; Biology; Population","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001690144,0.001303567,0.0009449067,0.000550058,0.0004632099,0.001079606,0.002585028,0.001139664,0.006495036],"category_scores_gemma":[0.006085959,0.0006599406,0.001503767,0.0006187249,0.0004665567,0.0006964397,0.001238495,0.001244345,0.002311235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000374752,"about_ca_system_score_gemma":0.001147175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02059071,"about_ca_topic_score_gemma":0.02322155,"domain_scores_codex":[0.9993027,0.0003710562,0.00003910474,0.0001482019,0.00008676627,0.00005215257],"domain_scores_gemma":[0.9977263,0.001747294,0.00007645696,0.0002484826,0.0001397196,0.00006170282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003169387,0.0001192227,0.01355777,0.0003039848,0.0006076493,0.0002925485,0.0002381887,0.919378,0.002556863,0.005002588,0.01580917,0.04181706],"study_design_scores_gemma":[0.00004318196,0.00004230073,0.0006177326,0.00001168698,0.00004085778,0.00007525121,0.00002046286,0.9923666,0.001089386,0.002084417,0.003587769,0.00002026018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1361715,0.0006362516,0.7658149,0.0009187188,0.0003498962,0.0001466136,0.007339513,0.08210309,0.006519437],"genre_scores_gemma":[0.5252019,0.0003394578,0.4565192,0.0004216078,0.00008312994,0.0003201955,0.004554233,0.008765776,0.003794633],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02059071,"threshold_uncertainty_score":0.04094172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04272691867439447,"score_gpt":0.3107500070951572,"score_spread":0.2680230884207627,"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."}}