{"id":"W4413109704","doi":"10.1093/bioadv/vbaf131","title":"Next generation biobanking ontology: introducing–omics contextual data to biobanking ontology","year":2024,"lang":"en","type":"article","venue":"Bioinformatics Advances","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; Simon Fraser University","funders":"King Fahad Medical City","keywords":"Biobank; Ontology; Computer science; Data science; Ontology-based data integration; Data discovery; Open Biomedical Ontologies; Data integration; Information retrieval; Metadata; Data management; World Wide Web; Data mining; Semantic Web; Suggested Upper Merged Ontology; Bioinformatics","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":[0.008143956,0.0006534371,0.0006275623,0.004486565,0.001704924,0.004431857,0.002137863,0.001317293,0.002628379],"category_scores_gemma":[0.01032529,0.0005515447,0.001742205,0.00505829,0.001868109,0.007986521,0.00544447,0.003272163,0.001688298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003188708,"about_ca_system_score_gemma":0.009362637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02005384,"about_ca_topic_score_gemma":0.0190255,"domain_scores_codex":[0.9952266,0.001278973,0.0007865163,0.0007370993,0.001606127,0.0003646732],"domain_scores_gemma":[0.9943731,0.001592363,0.0005128948,0.001355531,0.001709532,0.0004565545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001818678,0.000275434,0.006235251,0.001811336,0.0001945934,0.001339466,0.004071921,0.006551656,0.01291229,0.6554057,0.09909571,0.2119248],"study_design_scores_gemma":[0.00002572212,0.00001956931,0.002050433,0.0008171987,0.0000852533,0.0006755379,0.000740134,0.01724712,0.004768615,0.1234535,0.8500409,0.00007597222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006344174,0.001018035,0.9446732,0.007913041,0.0006529162,0.0008038608,0.01074301,0.006317003,0.02153479],"genre_scores_gemma":[0.03683569,0.001766304,0.9260707,0.002574081,0.000268929,0.0006850613,0.02518427,0.001199872,0.005415011],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02005384,"threshold_uncertainty_score":0.0430699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08394483396799426,"score_gpt":0.3364466195746183,"score_spread":0.2525017856066241,"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."}}