{"id":"W4240573566","doi":"10.1002/ange.201803540","title":"Effective Assignment of α2,3/α2,6‐Sialic Acid Isomers by LC‐MS/MS‐Based Glycoproteomics","year":2018,"lang":"en","type":"article","venue":"Angewandte Chemie","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital; Thermo Fisher Scientific (Canada)","funders":"Vetenskapsrådet; IngaBritt och Arne Lundbergs Forskningsstiftelse; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Knut och Alice Wallenbergs Stiftelse; Verband der Chemischen Industrie","keywords":"Glycoproteomics; Oxonium ion; Sialic acid; Chemistry; Glycosidic bond; Glycan; Mass spectrometry; Biochemistry; Glycoprotein; Characterization (materials science); Glycosylation; Computational biology; Chromatography; Ion; Organic chemistry; Biology; Nanotechnology; Enzyme; Materials science","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":[0.0007049248,0.0008483426,0.0003002586,0.0008076868,0.0002653917,0.0006413599,0.0003005966,0.0004098315,0.000972683],"category_scores_gemma":[0.0005854216,0.0002469405,0.0002619175,0.0003906944,0.0003523462,0.0005571322,0.0005225724,0.0006590199,0.0005036204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003048602,"about_ca_system_score_gemma":0.000459182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004547435,"about_ca_topic_score_gemma":0.0009635754,"domain_scores_codex":[0.9997144,0.00006085877,0.0000158287,0.00007488899,0.00009114202,0.00004275539],"domain_scores_gemma":[0.999823,0.00004902331,0.00003247615,0.00001968601,0.00004748246,0.000028461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007304499,0.00001087071,0.0003184911,0.00003520898,0.00001111759,0.0000272924,0.000009089065,0.00006455604,0.9958299,0.0001431386,0.00006993391,0.003407263],"study_design_scores_gemma":[0.00001131533,0.00007243916,0.002286203,0.000008860171,0.00002485787,0.000184614,0.00002284169,0.00389301,0.9919105,0.0001978522,0.001374666,0.00001283963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8268455,0.003048226,0.1609961,0.0004263196,0.0001264923,0.0003097208,0.003058114,0.0006913623,0.004498131],"genre_scores_gemma":[0.8503903,0.003141422,0.1423303,0.000348975,0.0000507826,0.000211662,0.001332061,0.0001355023,0.002058991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000972683,"threshold_uncertainty_score":0.003728092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007752058263636,"score_gpt":0.2688817043722444,"score_spread":0.2588041837896081,"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."}}