{"id":"W4401535430","doi":"10.1093/database/baae073","title":"Functional implications of glycans and their curation: insights from the workshop held at the 16th Annual International Biocuration Conference in Padua, Italy","year":2024,"lang":"en","type":"article","venue":"Database","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"National Institute of General Medical Sciences; National Heart, Lung, and Blood Institute; National Institutes of Health; National Human Genome Research Institute; Biotechnology and Biological Sciences Research Council; Novo Nordisk Fonden","keywords":"Data curation; Glycan; Function (biology); Glycosylation; Computer science; Data science; World Wide Web; Computational biology; Biology; Biochemistry; Genetics; Glycoprotein","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":[0.0001169503,0.00008021379,0.00005180479,0.00003803564,0.00009686432,0.00005880565,0.0001590444,0.00004902341,0.0001995787],"category_scores_gemma":[0.00009624092,0.00004633399,0.00002757513,0.0001428561,0.0001282775,0.0000322334,0.0001773208,0.0001071686,0.00001434511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001591561,"about_ca_system_score_gemma":0.0001054835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000159391,"about_ca_topic_score_gemma":0.003841981,"domain_scores_codex":[0.9993415,0.0000638354,0.0001590041,0.0002337161,0.0001233809,0.00007856189],"domain_scores_gemma":[0.9994261,0.0001107821,0.00003438955,0.0002885885,0.0001111976,0.00002891641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002561733,0.0001102772,0.0045456,0.00001890743,0.0001296704,0.000003493428,0.001535372,0.0001264681,0.9144975,0.02035663,0.04157631,0.0168436],"study_design_scores_gemma":[0.001177223,0.0001314231,0.1088366,0.0001520545,0.00002550033,0.00003725925,0.00372093,0.007477401,0.1651136,0.001868328,0.7110838,0.0003758842],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9596021,0.002590593,0.01450651,0.01792624,0.0002299935,0.0003703957,0.003908075,0.0000110313,0.0008551176],"genre_scores_gemma":[0.9919361,0.0002874667,0.00005878719,0.0001938735,0.0001675813,0.00005901405,0.006744834,0.000006078702,0.0005462249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7493839,"threshold_uncertainty_score":0.2185246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02936527249669314,"score_gpt":0.2912186749727225,"score_spread":0.2618534024760293,"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."}}