{"id":"W4308973189","doi":"10.1111/1758-5899.13158","title":"Finding synergies and trade‐offs when linking biodiversity and climate change through cooperative initiatives","year":2022,"lang":"en","type":"article","venue":"Global Policy","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research; York University","funders":"Planbureau voor de Leefomgeving; University of Oxford; Yale University","keywords":"Biodiversity; Climate change; Environmental resource management; Natural resource economics; Business; Biodiversity conservation; Environmental planning; Economics; Ecology; Geography; 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":[0.03393595,0.0005579484,0.000840301,0.003457993,0.002897229,0.01024229,0.001528473,0.002465965,0.02157683],"category_scores_gemma":[0.07918094,0.0005054999,0.0007840848,0.004452049,0.006582026,0.01415189,0.009480504,0.002655763,0.0006909937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004929195,"about_ca_system_score_gemma":0.003913189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003717535,"about_ca_topic_score_gemma":0.009077708,"domain_scores_codex":[0.9712261,0.0210943,0.000610728,0.001586776,0.00211471,0.003367355],"domain_scores_gemma":[0.8666071,0.1108333,0.009729929,0.004262553,0.003523332,0.005043899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002995373,0.003475526,0.3509082,0.002004142,0.001924445,0.00108721,0.02403991,0.03056809,0.002003135,0.3797744,0.006985439,0.1942341],"study_design_scores_gemma":[0.0006099466,0.002098031,0.1952062,0.002138703,0.001737641,0.0003740114,0.1456495,0.05141617,0.001408918,0.5650645,0.03406002,0.0002363549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8846347,0.002268642,0.01362557,0.009829227,0.0001020269,0.0003834572,0.0002822668,0.0000492033,0.0888249],"genre_scores_gemma":[0.9976052,0.000270214,0.001233035,0.0001492171,0.00001248225,0.0001464239,0.00003138571,0.000004737747,0.0005473282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03393595,"threshold_uncertainty_score":0.1794726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03402012681514814,"score_gpt":0.2714724386011923,"score_spread":0.2374523117860441,"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."}}