{"id":"W4226329328","doi":"10.1093/bioinformatics/btac195","title":"ELIXIR biovalidator for semantic validation of life science metadata","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Vlaamse regering; Fonds Wetenschappelijk Onderzoek; European Bioinformatics Institute","keywords":"Validator; Computer science; License; Schema (genetic algorithms); Elixir (programming language); Information retrieval; Metadata; JSON; Semantic integration; World Wide Web; Programming language; Semantic Web","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":[0.02466666,0.002508938,0.001437761,0.006342515,0.002580294,0.007486563,0.004270434,0.00242154,0.03149138],"category_scores_gemma":[0.05426424,0.001666862,0.00341407,0.003289551,0.001741905,0.008659867,0.01180542,0.003800094,0.03089865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002878796,"about_ca_system_score_gemma":0.007029591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006904767,"about_ca_topic_score_gemma":0.006757159,"domain_scores_codex":[0.9871091,0.00292837,0.001917293,0.002169005,0.005325114,0.0005511837],"domain_scores_gemma":[0.9682663,0.01102937,0.002460919,0.01040222,0.007197386,0.0006437761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003123556,0.0003872579,0.01391745,0.005561309,0.0007651137,0.001273996,0.002846041,0.006652706,0.02653859,0.08968955,0.5922801,0.2569643],"study_design_scores_gemma":[0.0003037792,0.0001664765,0.006507653,0.002308602,0.000249515,0.0009942097,0.000524088,0.04688341,0.07674799,0.04975083,0.8151497,0.0004138446],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.007914277,0.001048426,0.4026442,0.00139406,0.0005767332,0.0009628487,0.05829465,0.5065172,0.02064774],"genre_scores_gemma":[0.06131339,0.0009694166,0.4945009,0.002212796,0.0002057943,0.002196796,0.2972729,0.1279986,0.01332947],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03149138,"threshold_uncertainty_score":0.1304514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03119283094040965,"score_gpt":0.287908350116224,"score_spread":0.2567155191758143,"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."}}