Characterization of bacteria using its O-antigen with surface-enhanced Raman scattering
Bibliographic record
Abstract
The O-antigen determines the specificity of bacterial serotype, a sort of bacterial fingerprinting. In this work we report the extraction, purification and characterization of the O-antigen of two pathogenic bacteria, Escherichia coli O16 and Salmonella typhimurium. Molecular fingerprints found in the vibrational spectra represent a powerful analytical technique for identification (or differentiation) of molecular moieties in complex systems such as pathogens. In addition, advantages of vibrational Raman scattering are unique thanks to the high sensitivity and specificity achieved via surface-enhanced Raman scattering (SERS). SERS is used here to take advantage of characteristic vibrational frequency differences of O-antigens, thus allowing bacterial differentiation. Characteristic fundamental vibrational modes associated with the monosaccharide N-acetylglucosamine and deformations of the O-antigen chains provide the main spectroscopic differences between the O-antigens of E. coli O16 and S.typhimurium.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".