{"id":"W2092117678","doi":"10.1021/ac0512711","title":"Determination and Characterization of Site-Specific N-Glycosylation Using MALDI-Qq-TOF Tandem Mass Spectrometry:  Case Study with a Plant Protease","year":2006,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Agriculture and Agri-Food Canada","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Glycosylation; Glycan; Tandem mass spectrometry; Chromatography; Mass spectrometry; Glycoprotein; Glycopeptide; Oligosaccharide; Matrix-assisted laser desorption/ionization; N-linked glycosylation; Peptide; Biochemistry; Organic chemistry","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":[0.0008746256,0.000719687,0.0004691574,0.0004290275,0.0004011976,0.0007714902,0.0005559386,0.001659251,0.0002910749],"category_scores_gemma":[0.0008799759,0.0002100453,0.0004358019,0.0004458716,0.000458548,0.0005510878,0.0003312995,0.0005210427,0.000398997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003507981,"about_ca_system_score_gemma":0.0002105269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008990732,"about_ca_topic_score_gemma":0.0006392006,"domain_scores_codex":[0.9994766,0.0001085557,0.00003494061,0.0001288575,0.0001964273,0.00005460106],"domain_scores_gemma":[0.9997393,0.00008169973,0.00005463239,0.00002916379,0.00005839819,0.0000367693],"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":[0.00005954731,0.00005237286,0.001512073,0.0000741535,0.000008512412,0.001371724,0.00006349978,0.0002223834,0.9937108,0.00007959289,0.00002585738,0.002819429],"study_design_scores_gemma":[0.00001198323,0.0003633423,0.007966503,0.00001780133,0.0000420113,0.00991098,0.00009823476,0.006113684,0.9731362,0.0001697085,0.002147597,0.00002208547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9481578,0.003961534,0.04541603,0.000283164,0.0000231728,0.0001629522,0.0001974503,0.000134917,0.00166298],"genre_scores_gemma":[0.9216311,0.003240455,0.07344507,0.00009806135,0.00002596879,0.00004083586,0.0003516141,0.00004334502,0.001123586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001659251,"threshold_uncertainty_score":0.004625499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01547096379258233,"score_gpt":0.2636484803187951,"score_spread":0.2481775165262127,"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."}}