{"id":"W4410034255","doi":"10.1007/s10980-025-02095-z","title":"Silviculture shapes the spatial distribution of wildlife in managed landscapes","year":2025,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Saskatchewan; Ministry of Forests; Government of British Columbia; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Habitat Conservation Trust Foundation; University of Victoria","keywords":"Landscape ecology; Nature Conservation; Geography; Wildlife; Spatial distribution; Silviculture; Distribution (mathematics); Wildlife management; Wildlife conservation; Ecology; Environmental resource management; Agroforestry; Forestry; Environmental science; Habitat; Biology; Remote sensing","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002519462,0.00008417595,0.0001503193,0.00002674975,0.00009952419,0.000006239173,0.0002059764,0.0001456196,0.001078865],"category_scores_gemma":[0.0001038676,0.00005754368,0.00003567021,0.0002784095,0.00009583824,0.00006342112,0.0001131157,0.0001478223,0.00007045089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000374107,"about_ca_system_score_gemma":0.00001402872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002015325,"about_ca_topic_score_gemma":0.01775455,"domain_scores_codex":[0.9992377,0.0001272444,0.000208288,0.0001786415,0.00006835992,0.0001797269],"domain_scores_gemma":[0.9995893,0.0001945285,0.00007554251,0.0001172327,0.00000756402,0.00001579525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004126477,0.00005864522,0.9709006,0.000005592087,0.00001154818,0.000002834226,0.0001029198,0.0009068659,0.00004739446,0.0007959265,0.02640863,0.0007177613],"study_design_scores_gemma":[0.0004496368,0.00003706927,0.9875587,0.000005540555,0.00001534018,0.000001850934,0.0001117017,0.002597366,0.00002776559,0.0009989511,0.008138997,0.00005707071],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858734,0.00002823223,0.0001514014,0.007066206,0.0001883359,0.0001870942,0.000007373239,0.00001726465,0.006480698],"genre_scores_gemma":[0.9976961,0.00001845856,0.00001745373,0.001530341,0.00002751259,0.00003956284,0.00004764398,0.000002534229,0.0006203895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01826963,"threshold_uncertainty_score":0.9998343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003733141190053249,"score_gpt":0.2013524474219583,"score_spread":0.197619306231905,"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."}}