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Mass Spectrometry: An Outsourcing Guide

2009· article· en· W1956076416 on OpenAlexaff
Leroi V. DeSouza, K. W. Michael Siu, Ronald E. Pearlman

Bibliographic record

VenueCurrent Protocols Essential Laboratory Techniques · 2009
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsProteomeMass spectrometryOrganismComputational biologyProteomicsFocus (optics)Computer scienceData scienceChemistryChromatographyBiologyBiochemistryGenetics

Abstract

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Abstract Proteomics is the study of the proteins expressed from the genome of a cell or organism. Analytical mass spectrometry has recently become a powerful tool to study a cell or organism's proteome and is the focus of this chapter. Mass spectrometry can be used for both qualitative and quantitative analysis of proteomes. This chapter will focus on qualitative analysis, addressing questions of what proteins are present in a proteome and what post‐translational modifications may be associated with these proteins. The instrumentation required for mass spectrometric analysis is generally not available in a standard research laboratory or as part of an undergraduate laboratory, being associated in general with a core facility. We will not describe here details of specific operation of the instruments. Here we focus on the common types of analysis presently in routine use and on preparation of samples for routine biological mass spectrometric analysis that will allow most laboratories, including undergraduate and graduate teaching laboratories, to prepare and analyze samples in experiments designed to obtain proteomic information. Curr. Protoc. Essential Lab. Tech . 2:12.2.1‐12.1.18. © 2009 by John Wiley & Sons, Inc.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.201
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.364
Teacher spread0.346 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2009
Admission routes1
Has abstractyes

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