Rapid detection of microorganisms with nanoparticles and electron microscopy
Bibliographic record
Abstract
Rapid detection of microorganisms is highly desirable. A procedure has been developed based on interactions between gold nanoparticles and proteins of microorganisms (Escherichia coli, Rhodococcus rhodochrous, and Candida sp.) followed by scanning electron microscopy (SEM). The nanoparticle-cell interaction was confirmed by ultraviolet resonance Raman spectroscopy (UVRS) in the SEM focus. Cell suspensions in a buffer were interacted with gold nanoparticles (<10 nm in diameter) prepared from tetrachloroauric acid and sodium borohydride. Possible interference of elevated salt concentrations was eliminated by dialysis in deionized water. Small (10 microL) aliquots of cell-nanoparticle suspensions were dried on a silicon wafer and photographed under an SEM. Characteristic bacterial or yeast cell images in the micrographs indicated the actual presence of microorganisms in the suspension examined. This was further confirmed by UV resonance Raman spectroscopy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".