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Record W2039277347 · doi:10.5539/jfr.v2n3p104

Evaluation of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for Rapid Identification of Bacteria in Processed Soybean Products

2013· article· en· W2039277347 on OpenAlexvenueno aff
Yuko Furukawa, Mitsuru Katase, Kazunobu Tsumura

Bibliographic record

VenueJournal of Food Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsnot available
Fundersnot available
KeywordsBacteriaMass spectrometryChromatographyMatrix-assisted laser desorption/ionizationMatrix (chemical analysis)Chemistry16S ribosomal RNAMicrobiological cultureFood scienceDesorptionMicrobiologyBiologyGenetics

Abstract

fetched live from OpenAlex

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has recently been demonstrated as a rapid and reliable method for identifying bacteria in colonies grown on culture plates. Rapid identification of food spoilage bacteria is important for ensuring the quality and safety of food. To shorten the time of analysis, several researchers have proposed the direct MALDI-TOF MS tequnics for identification of bacteria in clinical samples such as urine and positive blood cultures. In this study, processed soybean products (total 26 test samples) were initially conducted a culture enrichiment step and bacterial cells were separated from interfering components. Harvested bacterial cells were determined by MALDI-TOF MS and 16S rRNA gene sequencing method. Six processed soybean products (23%) were increased bacterial cells after culture enrichiment step and they were sucessfully obtained the accurate identification results by MALDI-TOF MS-based method without colony formation.

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)0.007
metaresearch head score (Gemma)0.004
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 score0.046
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.075
GPT teacher head0.366
Teacher spread0.291 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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