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Record W125558691 · doi:10.1385/1-59745-167-3:237

Micromethods for the Characterization of Lipid A-Core and O-Antigen Lipopolysaccharide

2006· review· en· W125558691 on OpenAlexaff
Cristina L. Marolda, Piya Lahiry, Enrique D. Vinés, Soledad Saldı́as, Miguel A. Valvano

Bibliographic record

VenueHumana Press eBooks · 2006
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsWestern University
Fundersnot available
KeywordsLipopolysaccharideBacterial outer membraneBiogenesisLipid AEscherichia coliBacteriaGram-negative bacteriaMicrobiologyBacterial cell structureAntigenGeneMembraneChemistryBiologyBiochemistryGeneticsImmunology

Abstract

fetched live from OpenAlex

Methods for rapid and simple analysis of lipopolysaccharide (LPS) from bacterial whole-cell lysates or membrane preparations have contributed to advancing our knowledge of the genetics of the LPS biogenesis. LPS, a major constituent of the outer membranes in Gram-negative bacteria, has a complex mechanism of synthesis and assembly that requires the coordinated participation of many genes and gene products. This chapter describes a collection of methods routinely used in our laboratory for the characterization of LPS in Escherichia coli and other bacteria.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.015

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 head0.126
GPT teacher head0.352
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations100
Published2006
Admission routes1
Has abstractyes

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