{"id":"W4408572181","doi":"10.1002/pmic.202400238","title":"Monitoring Functional Posttranslational Modifications Using a Data‐Driven Proteome Informatic Pipeline","year":2025,"lang":"en","type":"article","venue":"PROTEOMICS","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Jane ja Aatos Erkon Säätiö; Vetenskapsrådet; Academy of Finland; Svenska Läkaresällskapet; Wellcome Trust","keywords":"Proteomics; Proteome; Computational biology; Pipeline (software); Computer science; In silico; Posttranslational modification; Glycoproteomics; Bioinformatics; Biology; Chemistry; Biochemistry; Gene","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":[0.00281906,0.001908031,0.001244725,0.003732627,0.0007292885,0.002262295,0.001214574,0.0007829209,0.001937393],"category_scores_gemma":[0.004226299,0.0006775812,0.00142555,0.002654472,0.0005078229,0.002417302,0.001447419,0.001092582,0.001176894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001078736,"about_ca_system_score_gemma":0.002684345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001910413,"about_ca_topic_score_gemma":0.002738826,"domain_scores_codex":[0.9989799,0.0001376373,0.000112159,0.0003558935,0.0003408189,0.00007361386],"domain_scores_gemma":[0.9981609,0.0006727013,0.0003174215,0.0002924787,0.0004404839,0.0001159572],"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":[0.003708262,0.001361112,0.03411957,0.002359796,0.001000043,0.00136269,0.0004502365,0.1078089,0.4490216,0.007710158,0.01754436,0.3735532],"study_design_scores_gemma":[0.0001415021,0.0005100019,0.01102434,0.00005330894,0.0002435327,0.0006820955,0.0001371559,0.7842354,0.1787706,0.01237033,0.01167171,0.0001601549],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1434291,0.001226934,0.7881801,0.001044004,0.00007614875,0.0007975864,0.01709515,0.04573715,0.002413874],"genre_scores_gemma":[0.323852,0.0007365037,0.6442008,0.000405295,0.00004584817,0.0005780449,0.02849777,0.0008229075,0.0008609009],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003732627,"threshold_uncertainty_score":0.01490879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07659382303852626,"score_gpt":0.3371935030312896,"score_spread":0.2605996799927634,"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."}}