{"id":"W2801259439","doi":"10.1111/geb.12747","title":"Global importance of large‐diameter trees","year":2018,"lang":"en","type":"article","venue":"Global Ecology and Biogeography","topic":"Forest ecology and management","field":"Environmental Science","cited_by":563,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Wilfrid Laurier University","funders":"National Natural Science Foundation of China; Natural Environment Research Council; Sight Research UK; Utah Agricultural Experiment Station; National Science Foundation","keywords":"Species richness; Diameter at breast height; Biomass (ecology); Hectare; Forestry; Biodiversity; Latitude; Ecology; Biology; Agroforestry; Geography","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":[0.0003001318,0.0001322918,0.000163122,0.0008721061,0.0001702385,0.0004955785,0.0001569164,0.0001538257,0.001998341],"category_scores_gemma":[0.001085678,0.00009433892,0.0001477193,0.00106654,0.0002887105,0.0005030934,0.0004602789,0.0001861473,0.0001913032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000133834,"about_ca_system_score_gemma":0.00007940966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002006736,"about_ca_topic_score_gemma":0.005811424,"domain_scores_codex":[0.9998079,0.00003736678,0.000008540084,0.00008680046,0.00003220776,0.00002717638],"domain_scores_gemma":[0.9987937,0.0003017755,0.0004726363,0.00009215245,0.0001903285,0.0001492078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002986245,0.000004566536,0.9858525,0.00003445269,0.00008124324,0.00003445312,0.0001531501,0.0005033438,0.001321688,0.0003314438,0.0002872028,0.0113661],"study_design_scores_gemma":[9.028833e-7,0.00000738443,0.9984645,0.000007331032,0.00001287951,0.00007810667,0.0001341366,0.0003712486,0.00008052719,0.00021171,0.0006291884,0.000002140554],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954953,0.0007615258,0.0006157339,0.00008674205,0.000007031687,0.000002355473,0.0006292143,0.00001216859,0.002389931],"genre_scores_gemma":[0.9992623,0.0001553847,0.0001489987,0.000008226265,0.000009294691,0.000001028759,0.0002873148,0.000002656093,0.0001248898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002006736,"threshold_uncertainty_score":0.006685078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003547030947613996,"score_gpt":0.2178704548985463,"score_spread":0.2143234239509323,"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."}}