{"id":"W2995552513","doi":"10.1088/1748-9326/ab60e1","title":"Integrated spatial analysis for human–wildlife coexistence in the American West","year":2019,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Division of Environmental Biology; Office of Experimental Program to Stimulate Competitive Research; National Aeronautics and Space Administration","keywords":"Wildlife; Geography; Environmental resource management; Environmental science; Environmental planning; Ecology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008378907,0.0002370092,0.0003323446,0.002628289,0.0004791924,0.001048027,0.0003880833,0.0001775097,0.002429541],"category_scores_gemma":[0.003186574,0.0001636706,0.0005259958,0.002624983,0.0003211652,0.0005987869,0.0008579874,0.0002650165,0.0001429076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007136199,"about_ca_system_score_gemma":0.0008370378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.115395,"about_ca_topic_score_gemma":0.1762303,"domain_scores_codex":[0.9995548,0.0002141654,0.00001987373,0.00008887663,0.00005605239,0.00006616893],"domain_scores_gemma":[0.9987229,0.000660405,0.0001346814,0.0001251922,0.000265516,0.00009141679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005821071,0.0001612833,0.9062424,0.00004438586,0.0006132623,0.0001421559,0.0006071039,0.01890929,0.002433483,0.002956436,0.00137286,0.06593526],"study_design_scores_gemma":[0.00002296646,0.00009400232,0.8273729,0.00001915829,0.0002496346,0.0001329243,0.00273752,0.164206,0.0006867051,0.003026832,0.00143147,0.00001997377],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994814,0.0001401289,0.003763442,0.00005976456,0.000003926715,0.000008113107,0.0003835011,0.00003473651,0.0007924755],"genre_scores_gemma":[0.9961515,0.00004363915,0.003239311,0.000004710332,0.00000373308,0.000007847323,0.0002660135,0.000009791873,0.0002734245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.115395,"threshold_uncertainty_score":0.2294465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03347898624165759,"score_gpt":0.3066149477302719,"score_spread":0.2731359614886144,"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."}}