{"id":"W3035532372","doi":"10.1111/ele.13535","title":"Designing optimal human‐modified landscapes for forest biodiversity conservation","year":2020,"lang":"en","type":"review","venue":"Ecology Letters","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":573,"is_retracted":false,"has_abstract":true,"ca_institutions":"ELUTIS Modelling and Consulting (Canada); Carleton University","funders":"Universidade Federal de Pernambuco; Universidad Nacional Autónoma de México; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Consejo Nacional de Ciencia y Tecnología; Carleton University","keywords":"Biodiversity; Ecology; Biodiversity conservation; Geography; Environmental resource management; Agroforestry; Environmental science; Biology","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":[0.0007280761,0.001141953,0.0008309401,0.001648284,0.0003160275,0.001349254,0.001469545,0.001393287,0.003464996],"category_scores_gemma":[0.001272442,0.0002749547,0.0007268092,0.001466706,0.0006476889,0.001793642,0.0009115101,0.00102292,0.0009692416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001178837,"about_ca_system_score_gemma":0.001389595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00228689,"about_ca_topic_score_gemma":0.004186075,"domain_scores_codex":[0.9997259,0.00007559745,0.00001906002,0.00004588694,0.00009780788,0.0000357357],"domain_scores_gemma":[0.9997008,0.0001449662,0.00005338325,0.00001831334,0.00006111775,0.00002141725],"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":[0.00003233925,0.0001108146,0.0005868945,0.0222622,0.0001785872,0.0001418898,0.0001105148,0.01836747,0.003417599,0.07065795,0.01330394,0.8708298],"study_design_scores_gemma":[0.00003704472,0.0001875242,0.00204813,0.01123559,0.0002709362,0.0008201267,0.0003221807,0.006668855,0.002601658,0.04794076,0.9277956,0.0000715737],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002027463,0.977688,0.01082148,0.0008773474,0.0002562767,0.00005580545,0.00007665445,0.00005129119,0.008145647],"genre_scores_gemma":[0.0232323,0.9619268,0.01277603,0.0003148999,0.0001157593,0.00008449968,0.000154903,0.0000233516,0.001371412],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003464996,"threshold_uncertainty_score":0.01159155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03887481610904939,"score_gpt":0.2562504646615488,"score_spread":0.2173756485524994,"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."}}