{"id":"W588681418","doi":"10.2307/jj.41003799.8","title":"Reducing Wildlife–Vehicle Collisions","year":2012,"lang":"en","type":"article","venue":"Princeton University Press eBooks","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fencing; Wildlife; Attractiveness; Population; Transport engineering; Geography; Visibility; Pedestrian; Warning signs; Habitat; Environmental resource management; Environmental science; Ecology; Computer science; Engineering; Environmental health; Psychology; Meteorology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001161232,0.00008835058,0.0000772294,0.00002921013,0.0002993858,0.00002253449,0.0002044942,0.0000503233,0.000273362],"category_scores_gemma":[0.00001438529,0.00009626094,0.00004636767,0.00004404979,0.00009059311,0.0004842139,0.0002859575,0.0001207331,0.0001185408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002037712,"about_ca_system_score_gemma":0.000009736993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001717833,"about_ca_topic_score_gemma":0.00001698596,"domain_scores_codex":[0.9992692,0.0000566053,0.00008937543,0.0001733037,0.0001589044,0.0002525569],"domain_scores_gemma":[0.9995024,0.00003662584,0.00006416376,0.0002418598,0.00001031407,0.0001446609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002749505,0.0007188959,0.7704821,0.00002942092,0.0001188318,0.0000270915,0.006179317,0.002577485,0.03615842,0.07091327,0.06853741,0.04398283],"study_design_scores_gemma":[0.0002088591,0.00001584464,0.07240678,0.00001249091,0.00002053811,0.000005018656,0.0001771302,0.00115072,0.003136666,0.000008651037,0.9227144,0.0001429767],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6658945,0.000004043628,0.0003622637,0.0001137818,0.0001301031,0.00010891,0.000004080223,0.00006201562,0.3333203],"genre_scores_gemma":[0.9488651,0.000008296267,0.0009780314,0.0002356818,0.00005323644,0.000001421359,0.000002528636,0.000007461097,0.0498482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8541769,"threshold_uncertainty_score":0.3925407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02233694026666059,"score_gpt":0.2182161514967828,"score_spread":0.1958792112301222,"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."}}