{"id":"W4311572563","doi":"10.1038/s41597-022-01774-9","title":"The global spectrum of plant form and function: enhanced species-level trait dataset","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"Algoma University; University of Waterloo; University of Saskatchewan; Université de Sherbrooke","funders":"Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig; Russian Science Foundation; Natural Environment Research Council; Consejo Nacional de Investigaciones Científicas y Técnicas; Newton Fund; Fondo para la Investigación Científica y Tecnológica; Inter-American Institute for Global Change Research; Universidad Nacional de Córdoba","keywords":"Trait; Biology; Categorical variable; Vascular plant; Specific leaf area; Plant species; Taxonomic rank; Botany; Ecology; Statistics; Mathematics; Species richness; Computer science","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":[0.00105616,0.001031811,0.0009721502,0.00376533,0.0004490451,0.001207944,0.001516157,0.001320377,0.006042625],"category_scores_gemma":[0.003092069,0.0003083475,0.001114557,0.004429328,0.0004114502,0.0008292774,0.001970049,0.001001761,0.007162382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005209255,"about_ca_system_score_gemma":0.0007210033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004425751,"about_ca_topic_score_gemma":0.00836944,"domain_scores_codex":[0.9990346,0.0001369666,0.0001170629,0.0003772325,0.0002215852,0.0001124153],"domain_scores_gemma":[0.9979762,0.0006015631,0.0003201128,0.0005320268,0.0003657546,0.0002042962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001223096,0.0005480726,0.1552254,0.007378362,0.001154504,0.0009606872,0.0007396042,0.01311258,0.02400026,0.00539512,0.7118185,0.07844388],"study_design_scores_gemma":[0.0003386387,0.0001900114,0.3057449,0.0004541103,0.0002917544,0.0009736228,0.0003839925,0.005945882,0.003812942,0.003331205,0.678344,0.0001888713],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01503154,0.0003804527,0.001309084,0.00007527126,0.00002464831,0.00002474036,0.9816204,0.0005675718,0.0009662739],"genre_scores_gemma":[0.009453119,0.00008840094,0.002282451,0.00004165241,0.000009710328,0.00008527461,0.9877332,0.00005723859,0.0002489364],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006042625,"threshold_uncertainty_score":0.02021462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03617426852601272,"score_gpt":0.2472785866775703,"score_spread":0.2111043181515576,"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."}}