{"id":"W6922113063","doi":"10.1111/geb.12729</p","title":"BioTIME: A database of biodiversity time series for the Anthropocene","year":2018,"lang":"en","type":"article","venue":"W&M Publish (College of William & Mary)","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Institute of Tropical Forestry; Natural Environment Research Council; Natural Sciences and Engineering Research Council of Canada; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig; Departament d'Universitats, Recerca i Societat de la Informació; Russian Science Foundation; Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul; Petrobras; Instituto Milenio de Oceanografía; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Agència de Gestió d'Ajuts Universitaris i de Recerca; Fundação de Amparo à Pesquisa do Estado de São Paulo; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Università di Pisa; Deutscher Akademischer Austauschdienst; University of St Andrews; Pacific Northwest Research Station; New Mexico State University; Ministerio de Educación, Cultura y Deporte; Oregon State University; National Science Foundation; University of Minnesota; U.S. Forest Service; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Gordon and Betty Moore Foundation; Deutsche Forschungsgemeinschaft; Andrew W. Mellon Foundation; U.S. Department of Agriculture; International Seafood Sustainability Foundation; Smithsonian Institution; Comisión Nacional de Investigación Científica y Tecnológica; Wellcome Trust","keywords":"Biodiversity; Metadata; Abundance (ecology); Sampling (signal processing); Range (aeronautics); Anthropocene; Invertebrate; Raw data; Time series","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003898787,0.0002207553,0.000308289,0.00006354902,0.0005370794,0.00001815335,0.0008535802,0.00009062384,0.004722192],"category_scores_gemma":[0.0001485822,0.0001740042,0.0001501744,0.0004661099,0.004588663,0.001046914,0.001416577,0.00008670356,0.0004246571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001296261,"about_ca_system_score_gemma":0.00001117214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004214642,"about_ca_topic_score_gemma":0.0000565842,"domain_scores_codex":[0.9983956,0.00004472422,0.0002891789,0.0004297066,0.0004817419,0.0003591144],"domain_scores_gemma":[0.9988608,0.0001507486,0.0002425336,0.0006091286,0.00004384971,0.00009291751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001562661,0.0002380254,0.2411004,0.00003897974,0.0001095157,0.000003168232,0.0001722251,0.000005377553,0.003957371,0.00002976891,0.7538682,0.0003207362],"study_design_scores_gemma":[0.001516967,0.001009158,0.7062073,0.00004722434,0.000252968,0.000006557782,0.00109686,0.0001129376,0.04882191,0.0001946803,0.2402142,0.0005192878],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9481691,0.0005004044,0.0003551915,0.008452161,0.001122178,0.002519809,0.01976068,0.0001277094,0.01899284],"genre_scores_gemma":[0.9092708,0.001390241,0.0719395,0.001368911,0.0003842728,0.0000622732,0.0003777615,0.00006730952,0.01513897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.513654,"threshold_uncertainty_score":0.9981202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181965443845965,"score_gpt":0.2096197125223095,"score_spread":0.1978000580838499,"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."}}