{"id":"W4322492266","doi":"10.1038/s41558-023-01608-5","title":"Climate change as a global amplifier of human–wildlife conflict","year":2023,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":241,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Wildlife; Climate change; Human–wildlife conflict; Subsistence agriculture; Livelihood; Biodiversity; Environmental resource management; Anthropocene; Wildlife conservation; Geography; Human systems engineering; Environmental planning; Ecology; Environmental science; Agriculture; Biology; Sociology","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":["insufficient_payload"],"category_scores_codex":[0.0004794956,0.0002256703,0.0002840609,0.00006882593,0.0002650282,0.0000195016,0.0003364813,0.0005510795,0.001763253],"category_scores_gemma":[0.0000648581,0.0002153724,0.0001076081,0.0007825186,0.000206411,0.0003341104,0.0004383965,0.0003462415,0.003135181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001184023,"about_ca_system_score_gemma":0.000005271815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000195527,"about_ca_topic_score_gemma":0.0003904678,"domain_scores_codex":[0.9981748,0.00007463391,0.0002937185,0.0004441419,0.0003502109,0.0006624795],"domain_scores_gemma":[0.9992312,0.00006211622,0.0002003232,0.0003601486,0.0000250252,0.0001211406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006583867,0.00009083236,0.9739071,0.00008128636,0.00001627415,0.00004379724,0.001255353,0.000001133787,0.0005234879,0.007581544,0.01351141,0.002921902],"study_design_scores_gemma":[0.0004513345,0.0001425237,0.9849711,0.00006513102,0.00002923462,0.00001098531,0.0002124061,0.00005323882,0.0001264555,0.0008826778,0.01282007,0.0002348497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798674,0.0001740225,4.129e-7,0.00408983,0.000633923,0.0005799345,0.0002448532,0.0002223676,0.01418726],"genre_scores_gemma":[0.9860725,0.0008315569,0.00003288412,0.01206433,0.0003942971,0.000253141,0.0001918069,0.00002511773,0.0001343265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01405293,"threshold_uncertainty_score":0.9991493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05364003512776658,"score_gpt":0.3200636260992435,"score_spread":0.2664235909714769,"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."}}