Monte Carlo Simulation and Optofluidic Techniques for Detecting Enterococcus faecalis and Enterococcus faecium
Bibliographic record
Abstract
This study presents a novel optofluidic system enhanced with Monte Carlo simulations for the optical characterization of bacterial suspensions, focusing on Enterococcus faecalis and Enterococcus faecium.The integration of optofluidics and advanced simulation techniques enables precise measurements of optical properties, including scattering, absorption, transmission, and refractive index (R.I.), which are critical for microbial detection.The system demonstrated the ability to distinguish between the two bacterial species, with R.I. values ranging from 1.405-1.410for E. faecalis and 1.395-1.400for E. faecium.Experimental results showed consistent trends of reduced light transmission with increasing bacterial concentrations (125-500 ppm) and extended optical path lengths (6-18 mm).Monte Carlo simulations validated the findings with error margins below 5%, highlighting the robustness of this approach.This method provides a scalable solution for bacterial diagnostics in clinical and environmental applications by achieving accurate, reproducible results and offering unique refractive index determination capabilities.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".