{"id":"W2586819609","doi":"10.1016/j.gloenvcha.2017.01.002","title":"Trees, forests and water: Cool insights for a hot world","year":2017,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":1172,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"VLIRUOS; Consortium of International Agricultural Research Centers; Vlaamse Interuniversitaire Raad; Belgisch Ontwikkelingsagentschap; KU Leuven","keywords":"Sustainability; Climate change; Environmental resource management; Ecoforestry; Environmental science; Climate change mitigation; Global warming; Greenhouse gas; Forest management; Business; Natural resource economics; Agroforestry; Ecology; Forest restoration; Forest ecology; Ecosystem; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.00005613723,0.0001655524,0.0001300522,0.00001520076,0.0004445152,0.0000838665,0.0002417932,0.00006292079,0.0002151056],"category_scores_gemma":[0.000002553009,0.0001271071,0.00004979974,0.00001738373,0.0002575431,0.0003651097,0.000394559,0.00005073286,0.0001932562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000199374,"about_ca_system_score_gemma":8.992428e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003926833,"about_ca_topic_score_gemma":0.004106071,"domain_scores_codex":[0.9990757,0.0000110736,0.0001206931,0.0003183614,0.0001668879,0.0003073023],"domain_scores_gemma":[0.9994757,0.000006512337,0.00006072476,0.0003237109,5.095674e-7,0.000132899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002014228,0.0002098192,0.9613993,0.0000147318,0.00004058307,0.00004283251,0.0006418924,0.0001094005,0.003997822,0.0008334965,0.0008593476,0.03164938],"study_design_scores_gemma":[0.0009103506,0.0001046553,0.9280029,0.00001188286,0.00003486687,0.00002721726,0.00001532622,0.008732672,0.0005204834,0.002194578,0.05912535,0.0003197122],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945763,0.0001028038,0.00009820731,0.0001932023,0.0001271289,0.000484576,0.0003170933,0.00002209569,0.004078528],"genre_scores_gemma":[0.9980189,0.00006837438,0.0002581764,0.0001773835,0.00006206558,0.0001104169,0.0001322795,0.00001114081,0.001161311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.058266,"threshold_uncertainty_score":0.5183275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767952425548806,"score_gpt":0.2181214038609222,"score_spread":0.2004418796054341,"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."}}