{"id":"W1977197340","doi":"10.1016/j.revpalbo.2012.08.005","title":"Wood specific gravity estimation based on wood anatomical traits: Inference of key ecological characteristics in fossil assemblages","year":2012,"lang":"en","type":"article","venue":"Review of Palaeobotany and Palynology","topic":"Forest ecology and management","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Consejo Nacional de Ciencia y Tecnología; Universidad El Bosque","keywords":"Fossil wood; Biomass (ecology); Ecology; Extant taxon; Paleoecology; Environmental science; Biology; Physical geography; Geography; Paleontology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001520628,0.00115686,0.001596859,0.005972053,0.0003871272,0.001161089,0.001365534,0.0008197895,0.0010348],"category_scores_gemma":[0.003575995,0.0005035011,0.0005838767,0.006173574,0.001050907,0.001441566,0.0009338626,0.0005433803,0.0008320116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002648808,"about_ca_system_score_gemma":0.0002527372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004009745,"about_ca_topic_score_gemma":0.00759554,"domain_scores_codex":[0.9989852,0.0002317022,0.00006508137,0.0004478195,0.0002202932,0.00004985704],"domain_scores_gemma":[0.9971237,0.001337094,0.0008144896,0.0002736284,0.0003567167,0.00009445438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001632273,0.0000824114,0.5871251,0.001028984,0.0005954144,0.0001471592,0.0004845366,0.007666779,0.0219234,0.001259387,0.001355849,0.3781678],"study_design_scores_gemma":[0.00001178065,0.00009507931,0.9678167,0.0001870642,0.0002593187,0.0008836444,0.0004295587,0.01867108,0.003122455,0.004883552,0.003550893,0.00008886563],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7622204,0.05821973,0.1680821,0.0003331587,0.000134141,0.00006682109,0.003479084,0.0005375914,0.006927039],"genre_scores_gemma":[0.9209742,0.01933543,0.05481813,0.0001040728,0.0002592021,0.00005542931,0.002981946,0.0001043298,0.001367212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005972053,"threshold_uncertainty_score":0.008041978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554912442355637,"score_gpt":0.2687780255777103,"score_spread":0.2532289011541539,"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."}}