{"id":"W4417239784","doi":"10.1007/s13280-025-02317-3","title":"Beyond kill or no-kill: Institutional analysis of lethal control decision-making in large carnivore management","year":2025,"lang":"en","type":"article","venue":"AMBIO","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"German Academic Exchange Service; Deutscher Akademischer Austauschdienst; Norges Forskningsråd; European Commission; HORIZON EUROPE Framework Programme; World Wildlife Fund","keywords":"Institutional analysis; Carnivore; Accountability; Legislature; Control (management); Democracy; Government (linguistics)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002768443,0.00007050956,0.0001692074,0.0001713435,0.00008918345,0.000006394395,0.0001484951,0.00006477598,0.001499482],"category_scores_gemma":[0.00006774038,0.00006125892,0.00006342049,0.0008895566,0.00009664273,0.0001007316,0.0001082296,0.00006902565,0.00008602324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001242244,"about_ca_system_score_gemma":0.00001694557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001811007,"about_ca_topic_score_gemma":0.005125818,"domain_scores_codex":[0.999235,0.0000396113,0.0002242913,0.000204658,0.000146966,0.0001494797],"domain_scores_gemma":[0.9996126,0.0001450477,0.00005927444,0.0001559439,0.00001002455,0.00001707437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001060671,0.0001371846,0.9856798,0.000005010545,0.0001740781,0.00002888976,0.00006523776,0.004808981,0.00002564853,0.003443694,0.001103996,0.004421402],"study_design_scores_gemma":[0.000594305,0.00002499636,0.9896159,0.00002375247,0.0001610287,4.692496e-7,0.00005267073,0.006014342,0.000005241257,0.0008299052,0.002614868,0.00006249559],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762087,0.00001594855,0.004530881,0.0002850449,0.0001571371,0.0001464891,0.00001816259,0.000009707764,0.01862788],"genre_scores_gemma":[0.9969417,0.000006619473,0.0007994832,0.001434527,0.000006542143,0.00001722361,0.00001258507,0.000001911354,0.0007793551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.020733,"threshold_uncertainty_score":0.9994133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003969418140618525,"score_gpt":0.2450696731801597,"score_spread":0.2411002550395412,"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."}}