{"id":"W4387765682","doi":"10.1111/cobi.14205","title":"Identifying global conservation priorities for terrestrial vertebrates based on multiple dimensions of biodiversity","year":2023,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Biodiversity; Convention on Biological Diversity; Geography; Environmental resource management; Prioritization; Measurement of biodiversity; Endangered species; Biodiversity conservation; Ecology; Biology; Environmental science; Habitat; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008601549,0.0003989968,0.0002554527,0.004103498,0.0004976585,0.001081137,0.0002614347,0.000209296,0.001682457],"category_scores_gemma":[0.002317096,0.00009355702,0.0002490981,0.003433067,0.0004489693,0.0009547836,0.001299437,0.0003817778,0.0001115201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008740154,"about_ca_system_score_gemma":0.0006329665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008114993,"about_ca_topic_score_gemma":0.02787855,"domain_scores_codex":[0.999625,0.0001018091,0.00002935009,0.00007402406,0.00009627234,0.0000736102],"domain_scores_gemma":[0.9987952,0.0002443097,0.0005357211,0.000063459,0.0002065399,0.0001547554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008170139,0.00003872573,0.8783473,0.0001985564,0.0001627985,0.0001474959,0.001007624,0.008527375,0.006540731,0.004001004,0.0014003,0.09954655],"study_design_scores_gemma":[0.000005241835,0.00007329174,0.9844066,0.00004976939,0.00004343738,0.0001158174,0.001792794,0.006731895,0.00053201,0.003377565,0.002848704,0.00002302322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793552,0.0008266993,0.01037095,0.0002761398,0.00001186147,0.00006740676,0.0008720317,0.00006098015,0.008158677],"genre_scores_gemma":[0.9901618,0.0001659577,0.008949214,0.00002861295,0.000007499189,0.00001981237,0.0004778973,0.00000575651,0.0001833744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008114993,"threshold_uncertainty_score":0.01613551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09237554912479974,"score_gpt":0.3009678295315295,"score_spread":0.2085922804067297,"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."}}