{"id":"W2127581180","doi":"10.2981/09-051","title":"Planning and prioritization strategies for phased highway mitigation using wildlife‐vehicle collision data","year":2011,"lang":"en","type":"article","venue":"Wildlife Biology","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada","funders":"Parks Canada; Montana State University","keywords":"Fencing; Wildlife; Environmental science; Prioritization; Environmental resource management; Cost–benefit analysis; Fence (mathematics); Transport engineering; Consistency (knowledge bases); Computer science; Business; Engineering; Ecology","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":[0.003497722,0.0007445123,0.0007168904,0.005649374,0.0008297205,0.001465523,0.001491521,0.0005835738,0.00372804],"category_scores_gemma":[0.007382216,0.0004572076,0.0005541182,0.00287214,0.0003110008,0.001177192,0.001108574,0.0006175996,0.0003635033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002892921,"about_ca_system_score_gemma":0.006610822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08370542,"about_ca_topic_score_gemma":0.1346093,"domain_scores_codex":[0.9983717,0.0007667883,0.000104182,0.0002218157,0.0002829306,0.0002526702],"domain_scores_gemma":[0.9942915,0.002835022,0.0007898559,0.0001741395,0.001328814,0.0005806305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0006652465,0.001170653,0.2856238,0.000838985,0.0003318872,0.0004436578,0.001044682,0.3851899,0.007715225,0.007109547,0.009038714,0.3008277],"study_design_scores_gemma":[0.0001586501,0.0008737544,0.1051359,0.0002215364,0.0002150939,0.000113708,0.005316484,0.8679399,0.00563319,0.006110937,0.00816569,0.0001151787],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8106198,0.0008438975,0.1603146,0.001596397,0.00004834517,0.005983386,0.004826646,0.001534097,0.01423271],"genre_scores_gemma":[0.8593361,0.0001833519,0.1367752,0.00006948053,0.00001116019,0.0007580392,0.001823932,0.00002392073,0.001018803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08370542,"threshold_uncertainty_score":0.1664364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09820117664375304,"score_gpt":0.3216562277091441,"score_spread":0.2234550510653911,"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."}}