{"id":"W2913698626","doi":"10.1002/ecs2.2597","title":"Wildlife mortality on roads and railways following highway mitigation","year":2019,"lang":"en","type":"article","venue":"Ecosphere","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Parks Canada","keywords":"Odocoileus; Wildlife; Fencing; Habitat; Geography; Ungulate; Ecology; Canis; Population; National park; Ursus; Environmental science; Fishery; Demography; Biology; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001272725,0.0001000358,0.00009632481,0.00000752038,0.0001001104,0.00004693344,0.00007500692,0.00005268203,0.006716392],"category_scores_gemma":[0.00001915129,0.00009391474,0.00005287281,0.00009742418,0.0000232711,0.000388637,0.00004466223,0.00009274596,0.00386491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008529874,"about_ca_system_score_gemma":0.000006313209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003767232,"about_ca_topic_score_gemma":0.0002232889,"domain_scores_codex":[0.9992387,0.0000300591,0.0001456034,0.0002602274,0.0001858981,0.000139543],"domain_scores_gemma":[0.9996245,0.00003537139,0.00005916267,0.0002181779,0.000003959055,0.0000588154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001569602,0.00007926549,0.88932,0.000008076578,0.00003364488,0.000004087513,0.0002091574,0.0009673524,0.004136456,0.0008609492,0.09516726,0.009198095],"study_design_scores_gemma":[0.0002908556,0.00007396149,0.9489473,0.00002622513,0.00001122932,0.00000191675,0.00009523783,0.003032037,0.0004798937,0.0003941595,0.04649289,0.0001543239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8909436,0.00001465496,0.00004432175,0.0006024627,0.0003358164,0.0001524252,0.00000231291,0.00004479787,0.1078596],"genre_scores_gemma":[0.9926224,0.000005421243,0.0003551904,0.001139203,0.00003976854,0.00001260122,0.00001115271,0.00001049694,0.005803762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1020559,"threshold_uncertainty_score":0.9969107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007432226280477164,"score_gpt":0.2231722132785439,"score_spread":0.2157399869980667,"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."}}