{"id":"W4410184804","doi":"10.1002/wsb.1593","title":"Wildlife crossing database platform: A transdisciplinary approach to developing a tool for landscape connectivity planning and public engagement","year":2025,"lang":"en","type":"article","venue":"Wildlife Society Bulletin","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Royal Roads University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Wildlife; Citizen science; Geography; Environmental resource management; Landscape planning; Public participation; Wildlife management; Public engagement; Environmental planning; Ecology; Biology; Environmental science; Political science; Public relations","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04877884,0.00108519,0.0005780455,0.005324773,0.003258712,0.01179975,0.003713666,0.002408355,0.01045427],"category_scores_gemma":[0.05347786,0.0009937921,0.00103306,0.003362687,0.005479303,0.01457789,0.01885982,0.004490733,0.002795147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003027766,"about_ca_system_score_gemma":0.00889423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002453149,"about_ca_topic_score_gemma":0.00352369,"domain_scores_codex":[0.9729883,0.01881106,0.001881019,0.001836976,0.003525499,0.0009572016],"domain_scores_gemma":[0.9326141,0.04757932,0.001937328,0.007198165,0.006856619,0.003814495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002757515,0.001110725,0.01068298,0.002353021,0.00009963408,0.002582384,0.3115329,0.002904061,0.01950309,0.1280766,0.05689659,0.4639823],"study_design_scores_gemma":[0.0001801337,0.0007808931,0.005694323,0.00394265,0.0001153874,0.002288142,0.1364897,0.01764116,0.00985929,0.06670131,0.7559807,0.0003263397],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.07469093,0.0003678733,0.8259343,0.01260588,0.000615176,0.006228527,0.001400371,0.006949719,0.07120723],"genre_scores_gemma":[0.1218736,0.0002744817,0.8616221,0.001134252,0.00006913351,0.003788088,0.0007585683,0.001072324,0.009407507],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04877884,"threshold_uncertainty_score":0.2579703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388142167697731,"score_gpt":0.2880495102573603,"score_spread":0.2492352934875872,"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."}}