Evaluation of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for Rapid Identification of Bacteria in Processed Soybean Products
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".