{"id":"W4406325587","doi":"10.1021/acs.jproteome.4c00576","title":"Characterization of 53 Multiplexed Targeted Proteomics Assays for Verification Studies in Cancer Cell Lines","year":2025,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"Jewish General Hospital; Genome British Columbia; Fonds de Recherche du Québec - Santé; Genome Canada","keywords":"Proteomics; Computational biology; Quantitative proteomics; Mass spectrometry; Biology; Biomarker; Multiplex; Orbitrap; Cancer; Tandem mass spectrometry; Peptide; Bioinformatics; Molecular biology; Chemistry; Biochemistry; Genetics; Chromatography; Gene","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":[0.004414045,0.0009936738,0.0007369719,0.001243017,0.0005000758,0.0009823724,0.0006013343,0.0007018305,0.0006023291],"category_scores_gemma":[0.002899684,0.000336369,0.0006203732,0.000911046,0.0004850173,0.0004653596,0.0005770568,0.0008321861,0.000464416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006370024,"about_ca_system_score_gemma":0.0007223646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008288713,"about_ca_topic_score_gemma":0.001789143,"domain_scores_codex":[0.9965441,0.0006050991,0.0004093968,0.0007570924,0.001480514,0.0002037361],"domain_scores_gemma":[0.9983383,0.0004338533,0.0003269796,0.0002554042,0.0005207156,0.0001247399],"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":[0.000112727,0.00007141304,0.002157578,0.00006444436,0.00003459539,0.00005161688,0.00005481211,0.0006186534,0.989111,0.0000906244,0.0001570908,0.007475498],"study_design_scores_gemma":[0.00001835106,0.0006501518,0.01399586,0.00002071315,0.00007595415,0.0003566266,0.00003766125,0.00464199,0.9773582,0.00008985856,0.002733196,0.0000212671],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8398541,0.003607519,0.1475051,0.0004371579,0.0001415525,0.001395548,0.003545556,0.00133211,0.002181394],"genre_scores_gemma":[0.7775694,0.002096099,0.2077823,0.0006419647,0.00006018276,0.001872338,0.007660239,0.0001571138,0.002160329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004414045,"threshold_uncertainty_score":0.02334404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1368773834784847,"score_gpt":0.4711668329990439,"score_spread":0.3342894495205592,"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."}}