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Record W2056850783 · doi:10.1016/j.jasms.2003.07.001

Experimental and theoretical investigation of the main fragmentation pathways of protonated H-Gly-Gly-Sar-OH and H-Gly-Sar-Sar-OH

2003· article· en· W2056850783 on OpenAlexaff
Béla Paizs, Sándor Suhai, Alex G. Harrison

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2003
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProtonationChemistryFragmentation (computing)IonTripeptideBranching (polymer chemistry)StereochemistryAmino acidBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The fragmentation pathways of protonated H-Gly-Gly-Sar-OH and H-Gly-Sar-Sar-OH are investigated by using both computational and experimental techniques. The main goal of these studies is to further investigate which factors determine the branching ratio of the b2-y1 (Paizs, B.; Suhai, S. Rapid Commun. Mass Spectrom. 2002, 16, 375.) and "diketopiperazine" (Cordero, M. M.; Houser, J. J.; Wesdemiotis, C. Anal. Chem. 1993, 65, 1594.) pathways of protonated tripeptides. Protonated H-Gly-Sar-Sar-OH represents a sensitive test for the branching ratio of the b2-y1 and "diketopiperazine" pathways since this ion cannot produce y1 ions on the b(-y1 channel but only b2 ions. Protonated H-Gly-Gly-Sar-OH and H-Gly-Sar-Sar-OH exhibit very different fragmentation behavior under the investigated experimental conditions. The former fragments forming mainly y1 ions (maximum abundance of the b2 and y2 ions is approximately 15%), while the latter produces mainly b2 ions while at larger internal energies the a2, y2, and y1 ions become also moderately abundant. Theoretical modeling and analysis of the main fragmentation pathways indicate that the majority of the b2 and y1 ions of protonated H-Gly-Gly-Sar-OH and the b2 ions of H-Gly-Sar-Sar-OH are formed on the b2-y1 pathway.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.258
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2003
Admission routes1
Has abstractyes

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Same venueJournal of the American Society for Mass SpectrometrySame topicMass Spectrometry Techniques and ApplicationsFrench-language works237,207