{"id":"W2912135339","doi":"10.1016/j.jenvman.2018.10.093","title":"How do landscape context and fences influence roadkill locations of small and medium-sized mammals?","year":2019,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Centre de Géomatique du Québec; Concordia University","funders":"Ministère des Transports; Concordia University; Ministère des Forêts, de la Faune et des Parcs","keywords":"Wildlife; Fence (mathematics); Context (archaeology); Geography; Vegetation (pathology); Wildlife management; Wildlife conservation; Ecology; Fishery; Environmental science; Biology; Archaeology; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002182488,0.0001122062,0.0001716485,0.00007044408,0.00005407143,0.00005947314,0.000145859,0.00003206954,0.0006505569],"category_scores_gemma":[0.000009310004,0.00009256655,0.00004302079,0.00006500255,0.0001543845,0.0005173038,0.0001715835,0.00009237233,0.0000275371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005962058,"about_ca_system_score_gemma":0.000003476344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003098073,"about_ca_topic_score_gemma":0.00002269123,"domain_scores_codex":[0.9991063,0.00003580974,0.0003068275,0.0001607443,0.0002748526,0.0001154428],"domain_scores_gemma":[0.9993782,0.00004579575,0.0003549935,0.0001417109,0.000004910665,0.00007437912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008246738,0.0001803238,0.953194,0.00003923005,0.000100108,0.000009543627,0.0003842022,0.0005620515,0.01262243,0.0001901958,0.0005245765,0.03211088],"study_design_scores_gemma":[0.0007467828,0.0002250876,0.9844496,0.00006489197,0.00005476998,0.00004158739,0.003573676,0.0001694148,0.000466627,0.0001896556,0.009907282,0.0001106774],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964927,0.0003098527,0.0001126671,0.001286874,0.00009266288,0.0002030803,0.000004430864,0.000002836589,0.001494937],"genre_scores_gemma":[0.996406,0.0008792448,0.001180988,0.000229152,0.00001591266,0.000004975525,0.000001319279,0.000006707549,0.00127572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0320002,"threshold_uncertainty_score":0.7123142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004493019739126024,"score_gpt":0.1812117291470115,"score_spread":0.1767187094078855,"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."}}