{"id":"W3083783622","doi":"10.1111/geb.13179","title":"Global root traits (GRooT) database","year":2020,"lang":"en","type":"article","venue":"Global Ecology and Biogeography","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":218,"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; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig; Russian Science Foundation; Office of Science; Robert Schalkenbach Foundation; Agence Nationale de la Recherche; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Deutsche Forschungsgemeinschaft; U.S. Department of Energy","keywords":"Trait; Biome; Root (linguistics); Biology; Ecology; Subspecies; Taxonomic rank; Taxon; Database; Geography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008261014,0.0001723389,0.0001976963,0.000005898706,0.0001697698,0.00003865911,0.0002122687,0.0001766443,0.0001465713],"category_scores_gemma":[0.00003334421,0.00007513358,0.0001390807,0.0008615641,0.0001827712,0.00007365532,0.0001331097,0.0000760526,0.00003032772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001279957,"about_ca_system_score_gemma":0.000009010806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002920531,"about_ca_topic_score_gemma":0.008442319,"domain_scores_codex":[0.9989009,0.0000656806,0.0001643816,0.0004019215,0.0001144274,0.0003527112],"domain_scores_gemma":[0.9995357,0.00003814686,0.00005174739,0.00003430881,0.00003627942,0.0003037867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008418482,0.00005774251,0.9783544,0.000004609942,0.00003881307,0.00002549586,0.000005375063,5.571053e-7,0.000745345,0.002843148,0.001366524,0.01647383],"study_design_scores_gemma":[0.0002467997,0.0004002355,0.9904372,0.000002289791,0.00003257718,0.00003277637,0.00006571443,0.0001415448,0.00002309162,0.001372412,0.007062702,0.000182714],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913805,0.0006190101,0.000002463971,0.004164612,0.0001253366,0.0001317317,0.001339839,0.000126756,0.002109787],"genre_scores_gemma":[0.9953265,0.00007032534,0.00008819842,0.004163566,0.0001595259,0.000007048133,0.0001826424,4.179063e-7,0.000001827275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01629111,"threshold_uncertainty_score":0.4711012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101888499565406,"score_gpt":0.2095751526160201,"score_spread":0.198556267620366,"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."}}