{"id":"W3025949524","doi":"10.1101/2020.05.17.095851","title":"Global Root Traits (GRooT) Database","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Natural Resources Canada; University of Saskatchewan; The Scarborough Hospital; University of Toronto; Canadian Forest Service","funders":"Biological and Environmental Research; Office of Science; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig; Russian Science Foundation; Deutsche Forschungsgemeinschaft; U.S. Department of Energy","keywords":"Trait; Biome; Root (linguistics); Biology; Taxonomic rank; Taxon; Ecology; Database; Ecosystem; 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":[0.001082368,0.001623282,0.001244634,0.007175989,0.0004195405,0.001771183,0.00198554,0.001230993,0.01587764],"category_scores_gemma":[0.004458616,0.0005057009,0.0009980535,0.0071361,0.0003269696,0.001514235,0.002548588,0.000851736,0.01669076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006779691,"about_ca_system_score_gemma":0.001300415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003765199,"about_ca_topic_score_gemma":0.004967666,"domain_scores_codex":[0.9988393,0.0001222702,0.0002870476,0.0003702399,0.0002509472,0.000130151],"domain_scores_gemma":[0.9975759,0.0006757235,0.0005495696,0.000448992,0.0005163958,0.000233488],"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":[0.003707849,0.0003312974,0.05600686,0.01928599,0.0008099236,0.001989478,0.001075331,0.007644071,0.02573248,0.01783448,0.7164668,0.1491155],"study_design_scores_gemma":[0.0004815825,0.000207115,0.07741138,0.00108112,0.0002980073,0.000852871,0.0004346066,0.007091098,0.007865972,0.009022217,0.8950663,0.0001876947],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006539796,0.000434004,0.003194405,0.00004655682,0.00001910906,0.00007694963,0.9824942,0.005172563,0.00202241],"genre_scores_gemma":[0.008101676,0.0002140712,0.006290353,0.00005693867,0.00000929625,0.0001773771,0.9840553,0.0006108019,0.0004841892],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01587764,"threshold_uncertainty_score":0.05311596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02070707829466719,"score_gpt":0.2163763750455621,"score_spread":0.1956692967508949,"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."}}