{"id":"W2041461813","doi":"10.1021/pr0155174","title":"Peptide End Sequencing by Orthogonal MALDI Tandem Mass Spectrometry","year":2002,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Muscular Dystrophy Canada","funders":"","keywords":"Mass spectrometry; Peptide mass fingerprinting; Tandem mass spectrometry; Bottom-up proteomics; Chemistry; Peptide; Tandem mass tag; Protein mass spectrometry; Proteomics; Mass spectrum; Chromatography; Peptide sequence; Top-down proteomics; Fragmentation (computing); Electrospray; Sample preparation in mass spectrometry; Isobaric labeling; Analytical Chemistry (journal); Quantitative proteomics; Electrospray ionization; Biochemistry; Biology","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":[0.001356417,0.001032862,0.0007075226,0.001145442,0.0004197339,0.0009323353,0.0008161095,0.0007075321,0.002491191],"category_scores_gemma":[0.001954772,0.0004541759,0.0004709488,0.0008197341,0.0003601259,0.001092566,0.001335274,0.001116709,0.003458667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000255819,"about_ca_system_score_gemma":0.0006981302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000259405,"about_ca_topic_score_gemma":0.000408821,"domain_scores_codex":[0.9988214,0.0002491529,0.0001313555,0.0002785785,0.0004120197,0.000107512],"domain_scores_gemma":[0.9990357,0.0002599873,0.000156682,0.0001327284,0.0003312599,0.00008363797],"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":[0.0002427759,0.00006596994,0.0003732092,0.0001538361,0.00003029685,0.00009611147,0.00003630363,0.0003234079,0.9539465,0.0008262582,0.000802793,0.0431025],"study_design_scores_gemma":[0.00009715294,0.0004252638,0.001883297,0.00003426984,0.00005126944,0.00150027,0.00003640738,0.0167392,0.9564264,0.001829235,0.0209057,0.0000714794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07581635,0.00239101,0.910892,0.0002497438,0.0001822215,0.0005368622,0.001540508,0.004425887,0.003965443],"genre_scores_gemma":[0.1050093,0.003711698,0.8826215,0.00034048,0.00009481253,0.0007645404,0.003038011,0.0004694837,0.003950133],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002491191,"threshold_uncertainty_score":0.008333921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07018039688961876,"score_gpt":0.3422819176072281,"score_spread":0.2721015207176094,"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."}}