{"id":"W2071911878","doi":"10.1016/j.jprot.2010.02.013","title":"Development and application of mass spectrometric methods for the analysis of progranulin N-glycosylation","year":2010,"lang":"en","type":"article","venue":"Journal of Proteomics","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Royal Victoria Hospital","funders":"Yorkshire Forward","keywords":"Glycosylation; Glycan; PNGase F; Chemistry; Glycoprotein; N-linked glycosylation; Biochemistry; Glycopeptide; Glycomics","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":[0.001010701,0.00005440807,0.0002580465,0.0004298574,0.00003444623,0.000006483107,0.0000590985,0.00003770109,0.000006825245],"category_scores_gemma":[0.0002062834,0.0000320966,0.0001257645,0.0006406791,0.00004500954,0.00004014934,0.000009920259,0.0001153403,1.74008e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002868237,"about_ca_system_score_gemma":0.0001734944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005482201,"about_ca_topic_score_gemma":0.000004150319,"domain_scores_codex":[0.9992628,0.00002550034,0.0003619061,0.00006312865,0.0002046243,0.0000820149],"domain_scores_gemma":[0.9988208,0.0001728161,0.0004450989,0.0001118892,0.0003695121,0.00007989231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002040055,0.0007849856,0.1054527,0.0002408156,0.03505777,0.000002934942,0.0003864096,0.00004284421,0.295414,0.0005586621,0.00000720136,0.5600116],"study_design_scores_gemma":[0.003318121,0.0007847931,0.4810783,0.00003333015,0.01031762,0.00002598225,0.0001264592,0.02067445,0.4815584,0.001301834,0.0006875175,0.00009319775],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6604465,0.0009272782,0.3376763,0.0001592259,0.00001532215,0.0007568068,0.000004379207,0.000001478247,0.00001277844],"genre_scores_gemma":[0.5311864,0.00005468508,0.4687005,0.00000236149,0.00002257392,0.0000239109,0.000004406734,0.000003460458,0.000001688241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5599184,"threshold_uncertainty_score":0.1308861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02927175710028403,"score_gpt":0.3945489140333938,"score_spread":0.3652771569331097,"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."}}