{"id":"W2118897204","doi":"10.1074/mcp.m900456-mcp200","title":"Synthetic Peptide Arrays for Pathway-Level Protein Monitoring by Liquid Chromatography-Tandem Mass Spectrometry","year":2010,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kinexus Bioinformatics Corporation (Canada); University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Chemistry; Tandem mass spectrometry; Mass spectrometry; Computational biology; Shotgun; Proteomics; Multiplex; Phosphoproteomics; Chromatography; Peptide; Biology; Bioinformatics; Kinase; Protein phosphorylation; Protein kinase A; Biochemistry","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":[0.0007552678,0.0006058109,0.0004050747,0.0003904486,0.0002293096,0.0005406152,0.0005583155,0.0004418277,0.00115019],"category_scores_gemma":[0.0007202249,0.0002729571,0.0002645726,0.0003740616,0.0003191424,0.0004893918,0.0004269561,0.0006985771,0.0007657705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003330428,"about_ca_system_score_gemma":0.0003215668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001238765,"about_ca_topic_score_gemma":0.0003365741,"domain_scores_codex":[0.9992712,0.0002007546,0.00004744756,0.0001484946,0.0002989681,0.0000331432],"domain_scores_gemma":[0.9997414,0.0001029352,0.00004847692,0.00003119499,0.0000483351,0.00002757131],"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":[0.00004289301,0.00002195366,0.00009140958,0.00004518841,0.000007558441,0.00001822351,0.00000499141,0.000377415,0.9919211,0.0002996359,0.0001433308,0.007026378],"study_design_scores_gemma":[0.00002124392,0.0002045954,0.000591234,0.000006614185,0.00001754493,0.000161321,0.000007881034,0.009647737,0.9837151,0.0005387052,0.005072411,0.00001552429],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1922665,0.004917471,0.7942231,0.0004643271,0.000252372,0.000588928,0.001760357,0.002563322,0.002963479],"genre_scores_gemma":[0.2530537,0.002557463,0.7397345,0.0003693,0.00009319672,0.0008295767,0.001542328,0.0001176537,0.001702389],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00115019,"threshold_uncertainty_score":0.003994286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009809578420289681,"score_gpt":0.2330581205582195,"score_spread":0.2232485421379298,"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."}}