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Record W2316619196 · doi:10.1021/ac300648g

Liquid Chromatography–Atmospheric Pressure Electron Capture Dissociation Mass Spectrometry for the Structural Analysis of Peptides and Proteins

2012· article· en· W2316619196 on OpenAlexafffund
Damon B. Robb, Jason C. Rogalski, Juergen Kast, Michael W. Blades

Bibliographic record

VenueAnalytical Chemistry · 2012
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsChemistryMass spectrometryElectron-capture dissociationChromatographyDissociation (chemistry)Atmospheric pressureLiquid chromatography–mass spectrometryTandem mass spectrometryOrganic chemistry

Abstract

fetched live from OpenAlex

Atmospheric pressure electron capture dissociation (AP-ECD) is an emerging technique with the potential to be a more accessible alternative to conventional ECD/electron transfer dissociation (ETD) methods because it can be implemented using a stand-alone ion source device suitable for use with any existing or future electrospray ionization mass spectrometer. With AP-ECD, no modification of the main instrument is required, so it may easily be retrofitted to instruments not originally equipped with ECD/ETD capabilities. Here, we present our first purpose-built AP-ECD source and demonstrate its use in conjunction with capillary LC for the analysis of substance P, a tryptic digest of bovine serum albumin, and a phosphopeptide mixture. Quality ECD spectra were obtained for all the samples at the low femtomole level, proving that LC-AP-ECD-MS is suitable for the structural analysis of peptides and protein digests, in this case using an unmodified quadrupole time-of-flight mass spectrometer built ca. 2002.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.006
GPT teacher head0.255
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2012
Admission routes2
Has abstractyes

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