{"id":"W4392619868","doi":"10.1111/gcb.17224","title":"Global patterns of tree wood density","year":2024,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Forest ecology and management","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; Horizon 2020 Framework Programme; International Max Planck Research School for Environmental, Cellular and Molecular Microbiology","keywords":"Evergreen; Deciduous; Environmental science; Edaphic; Vegetation (pathology); Physical geography; Ecology; Geography; Soil science; Biology","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":[0.0003008899,0.0002055448,0.0002441602,0.0009640345,0.00008646295,0.0003612757,0.0001370631,0.0001547927,0.0007130506],"category_scores_gemma":[0.00048205,0.0001054087,0.0002915668,0.001050011,0.0001700328,0.0003808247,0.0002922628,0.0001141854,0.0001982867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001498407,"about_ca_system_score_gemma":0.00007803531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004040587,"about_ca_topic_score_gemma":0.004273063,"domain_scores_codex":[0.9998802,0.00001285501,0.000006319767,0.0000649998,0.00001637351,0.00001923211],"domain_scores_gemma":[0.9997281,0.00006273164,0.00005578021,0.00004759323,0.00008754761,0.0000181929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000774007,0.00001625576,0.9242642,0.00005611154,0.0002410194,0.00009512671,0.0002465009,0.02668516,0.006941017,0.0005239699,0.0009682007,0.03988503],"study_design_scores_gemma":[0.000002326471,0.00001309204,0.981685,0.000007338017,0.00003105499,0.00006354993,0.00009782147,0.01659678,0.0005438921,0.0002198837,0.0007308799,0.00000840017],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948833,0.0001902922,0.002239465,0.00002085909,0.000002178089,0.000003025789,0.001682452,0.00007486039,0.0009035904],"genre_scores_gemma":[0.996767,0.00006790763,0.0006373217,0.000005804004,0.000002527995,0.000004374237,0.002331502,0.00001000669,0.0001735459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004040587,"threshold_uncertainty_score":0.00803417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01991382129861264,"score_gpt":0.2594411312522021,"score_spread":0.2395273099535895,"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."}}