{"id":"W2558103134","doi":"10.1021/acs.jproteome.6b00825","title":"Opposite Electron-Transfer Dissociation and Higher-Energy Collisional Dissociation Fragmentation Characteristics of Proteolytic K/R(X)<sub><i>n</i></sub> and (X)<i><sub>n</sub></i>K/R Peptides Provide Benefits for Peptide Sequencing in Proteomics and Phosphoproteomics","year":2016,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Horizon 2020; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; European Molecular Biology Organization","keywords":"Electron-transfer dissociation; Fragmentation (computing); Dissociation (chemistry); Chemistry; Electron-capture dissociation; Atomic physics; Electron transfer; Crystallography; Mass spectrometry; Physics; Tandem mass spectrometry; Physical chemistry; Biology; Chromatography","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":[0.0006063363,0.0003852384,0.0002619514,0.0003314249,0.0002164666,0.0004679336,0.0004083111,0.0006109093,0.001651337],"category_scores_gemma":[0.0007317233,0.0001637433,0.0002268744,0.0003776005,0.0005300567,0.0007034236,0.0002725709,0.0005405093,0.0005747103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002196813,"about_ca_system_score_gemma":0.0001802356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003582875,"about_ca_topic_score_gemma":0.0003505922,"domain_scores_codex":[0.9996278,0.00005519563,0.00003421845,0.0001107912,0.0001269526,0.00004502367],"domain_scores_gemma":[0.9993389,0.000233489,0.0001918246,0.00006154158,0.0001140822,0.00006011982],"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":[0.0001979573,0.00003745875,0.001316068,0.00007458974,0.00001731481,0.00009986057,0.00004040238,0.00009305641,0.9932207,0.0001276115,0.00004846552,0.004726462],"study_design_scores_gemma":[0.00001300703,0.0002070222,0.01922013,0.0000045325,0.00001210412,0.001875871,0.00005319488,0.0009620326,0.9762674,0.0001324605,0.001238916,0.00001328692],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769614,0.002250511,0.01753777,0.0001299412,0.00002283805,0.00005502965,0.0004757083,0.0001420367,0.002424787],"genre_scores_gemma":[0.9611127,0.001898705,0.033314,0.0002222221,0.00001722529,0.00008542883,0.001042695,0.00006883831,0.002238203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001651337,"threshold_uncertainty_score":0.005524278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02340798294110194,"score_gpt":0.2848064578476508,"score_spread":0.2613984749065488,"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."}}