{"id":"W4402602294","doi":"10.1038/s44185-024-00053-7","title":"Contextualising samples: supporting reference genomes of European biodiversity through sample and associated metadata collection","year":2024,"lang":"en","type":"article","venue":"npj Biodiversity","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"European Social Fund; Leibniz-Gemeinschaft; HORIZON EUROPE European Research Council; Biotechnology and Biological Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; HORIZON EUROPE Framework Programme; Directorate for Biological Sciences; Science for Life Laboratory; Agencia Estatal de Investigación; Fundação para a Ciência e a Tecnologia; Leibniz-Institut für Zoo- und Wildtierforschung; James S. McDonnell Foundation; Norges Forskningsråd; Ministerio de Ciencia e Innovación; Rural Development Administration; UK Research and Innovation; Staatssekretariat für Bildung, Forschung und Innovation; Deutsche Forschungsgemeinschaft","keywords":"Workflow; Metadata; Sample (material); Biodiversity; Data science; Resource (disambiguation); Genome; Environmental resource management; Biology; World Wide Web; Computer science; Ecology; Database","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":[0.1103526,0.0007739658,0.0008251994,0.006454056,0.003874679,0.01151329,0.0043577,0.002348504,0.005737581],"category_scores_gemma":[0.1614524,0.0009663707,0.001098532,0.007892231,0.003418414,0.0121264,0.01720511,0.003319713,0.004140355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003800329,"about_ca_system_score_gemma":0.02301932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01726297,"about_ca_topic_score_gemma":0.02365418,"domain_scores_codex":[0.9355508,0.03619326,0.009233828,0.005847914,0.01152863,0.001645612],"domain_scores_gemma":[0.8668073,0.04100931,0.008391403,0.04938026,0.03074821,0.00366341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004812256,0.0002410336,0.02557293,0.003589133,0.0002021335,0.001272372,0.06510498,0.003245794,0.02207295,0.1249065,0.1017428,0.6515682],"study_design_scores_gemma":[0.00005590423,0.00008356639,0.01026017,0.002604667,0.00007134756,0.0005640056,0.01225293,0.001222979,0.01094052,0.04168437,0.9200751,0.0001844198],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0297835,0.003329482,0.8677929,0.01959891,0.00229669,0.00377341,0.01498592,0.005478991,0.05296012],"genre_scores_gemma":[0.05031948,0.001392099,0.9227793,0.002787404,0.0002542239,0.001301354,0.01517975,0.001915608,0.004070856],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1103526,"threshold_uncertainty_score":0.5836074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05822461163247484,"score_gpt":0.2473578766936031,"score_spread":0.1891332650611283,"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."}}