{"id":"W3108258707","doi":"10.1038/s41598-020-77321-6","title":"Railway mortality for several mammal species increases with train speed, proximity to water, and track curvature","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Pacific Kansas City; Parks Canada","keywords":"Habitat; Wildlife; Ecology; Mammal; Spatial ecology; Track (disk drive); Geography; Environmental science; Biology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003554179,0.000204387,0.0001172655,0.0007585023,0.0003505148,0.0003284095,0.0002345604,0.0001971512,0.001228654],"category_scores_gemma":[0.0011785,0.0001108862,0.0002976322,0.0007213482,0.0002881064,0.0002834925,0.0003782304,0.0002480995,0.0001687306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000477442,"about_ca_system_score_gemma":0.0002971154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04126528,"about_ca_topic_score_gemma":0.1479779,"domain_scores_codex":[0.9997703,0.00003878698,0.00001943455,0.00005285458,0.00008153274,0.00003707403],"domain_scores_gemma":[0.998389,0.0001485449,0.001112933,0.00006615544,0.0001915056,0.00009193292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008156294,0.000005036207,0.9980574,0.00000452324,0.00001871742,0.0000153352,0.00004712029,0.00005439239,0.0002224603,0.000005138026,0.00003909928,0.001522523],"study_design_scores_gemma":[1.488078e-7,0.000009560746,0.9997649,0.000001270868,0.000004349254,0.00003149138,0.00005631238,0.00005642985,0.00002542047,0.000003024379,0.0000465582,6.585907e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990914,0.0001214711,0.0001980966,0.00002572381,0.000001932608,0.000004745452,0.0001840411,0.000006378071,0.0003662119],"genre_scores_gemma":[0.9988355,0.0001549537,0.0003494323,0.00001300909,0.000006141577,0.000005077029,0.0003564412,0.000001428753,0.0002780818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04126528,"threshold_uncertainty_score":0.0820502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521369635136288,"score_gpt":0.2378083602486914,"score_spread":0.2125946638973285,"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."}}