{"id":"W2321794224","doi":"10.1021/ac101831t","title":"Methylamidation for Sialoglycomics by MALDI-MS: A Facile Derivatization Strategy for Both α2,3- and α2,6-Linked Sialic Acids","year":2010,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Institute for Biological Sciences","funders":"National Research Council Canada; National Natural Science Foundation of China","keywords":"Chemistry; Sialic acid; Derivatization; Glycan; Fetuin; Chromatography; Sialidase; Mass spectrometry; Matrix-assisted laser desorption/ionization; Electrospray ionization; Glycoprotein; Carboxylic acid; Biochemistry; Organic chemistry; Desorption; Neuraminidase","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":[0.000414228,0.001023068,0.0003088859,0.0002233968,0.0002325557,0.0002380046,0.0004221536,0.0005220688,0.0007582693],"category_scores_gemma":[0.0003849724,0.0003003219,0.0003247626,0.0001997059,0.0002613565,0.0004290968,0.0004937664,0.0008540815,0.0006268934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002633673,"about_ca_system_score_gemma":0.0003399503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005929425,"about_ca_topic_score_gemma":0.0006954058,"domain_scores_codex":[0.9997237,0.00004798611,0.00001876401,0.0000684397,0.00009913516,0.00004201171],"domain_scores_gemma":[0.9998492,0.00002888713,0.00003784539,0.00002121254,0.00003916832,0.00002352838],"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":[0.00001847435,0.000003812587,0.00006189558,0.00002077319,0.000003815574,0.00002167367,0.000009325526,0.00002300208,0.9984152,0.0000281201,0.00001173495,0.001382192],"study_design_scores_gemma":[0.000004060326,0.00005758366,0.0006738211,0.000002668158,0.000007513129,0.0002207363,0.000008541288,0.0005964967,0.9973545,0.00002814951,0.001039307,0.000006690631],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7904469,0.006401764,0.1984626,0.0004526667,0.0001201773,0.0002892429,0.0004807706,0.0005232639,0.002822716],"genre_scores_gemma":[0.8121693,0.005456152,0.177959,0.0003542659,0.00004849429,0.0002415225,0.000633399,0.0001260333,0.003011721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001023068,"threshold_uncertainty_score":0.002536654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01844140209811452,"score_gpt":0.3078138063326628,"score_spread":0.2893724042345482,"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."}}