{"id":"W4416199408","doi":"10.1021/acs.jproteome.5c00415","title":"Use of Synthetic Standard Peptides in Standardized Digests to Evaluate Both Sample and Instrument Suitability in Proteomics","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":"IONICS Mass Spectrometry (Canada)","funders":"","keywords":"Proteome; Mass spectrometry; Peptide; Sample (material); Proteomics; Quantitative proteomics; Sample preparation; Label-free quantification","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":[0.009780093,0.001241067,0.0005976645,0.0009886967,0.0006874796,0.001182578,0.000737189,0.001341781,0.0009558831],"category_scores_gemma":[0.01191976,0.0006167582,0.0006381506,0.001605828,0.001467028,0.0009940719,0.0007944347,0.0008546298,0.0004755827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006106997,"about_ca_system_score_gemma":0.0006508652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004246354,"about_ca_topic_score_gemma":0.0008545227,"domain_scores_codex":[0.9903904,0.003777937,0.001298354,0.001442542,0.002704618,0.0003861718],"domain_scores_gemma":[0.9911469,0.004921763,0.0009296145,0.001326638,0.001463056,0.0002120371],"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":[0.0003494688,0.0001634058,0.001578994,0.0001450898,0.00004666664,0.00005403264,0.00009883154,0.001068921,0.9928539,0.0001747075,0.00004499171,0.003420968],"study_design_scores_gemma":[0.00001624627,0.0009853808,0.003538677,0.00001300177,0.00004575507,0.0001041571,0.00004284937,0.003208113,0.9911292,0.0001460121,0.0007503156,0.00002034769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8141202,0.001584818,0.1800931,0.0001503575,0.0001415161,0.001402652,0.0006305267,0.000462435,0.001414399],"genre_scores_gemma":[0.6757044,0.001529988,0.3154728,0.0005147645,0.00006720552,0.002557377,0.00236202,0.0003957142,0.00139579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009780093,"threshold_uncertainty_score":0.05172271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08072733437655918,"score_gpt":0.4157197443853618,"score_spread":0.3349924100088026,"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."}}