Standardization and internal validation of a bacteria identification method utilizing focal-plane-array fourier transformed infrared spectroscopy
Bibliographic record
Abstract
Food-borne diseases collectively affect significant portions of the world's population. In Canada recent food-borne outbreaks and diseases resulted in significant expenses and resource allocations. Consequently, finding methods that can detect and identify microorganisms in faster, reliable and cost effective ways is a pressing need. Microbial identification methods based on the infrared spectral analysis of microorganisms have been shown to be potentially viable. The recent development of focal plane array Fourier transform infrared (FPA-FTIR) spectroscopy provided the means of acquiring thousands of infrared spectra in the time it takes to record a single spectrum. The increased number of infrared spectra of each organism provides infrared-based microbial differentiation and identification methods with added reliability. Accordingly, we generated a comprehensive standardized and internally validated the FPA-FTIR based bacteria identification method. All infrared spectra were collected from bacterial colonies, lifted from agar and deposited on zinc selenide (ZnSe) slides, on a Agilent Excalibur FTIR spectrometer equipped with a UMA-600 infrared microscope and a 32 x 32 (1024 pixels) mercury-cadmium-telluride focal-plane-array detector and operated under Resolutions Pro 4.0 software (Agilent Technologies, Melbourne, Australia). The effect of growth media formulations, growth time and inactivation techniques on the spectral reproducibility of microorganism was tested. Most of these variables showed some degree of influence on spectral variability, therefore a single combination of these was recommended in the form of a laboratory protocol for consistent microbial preparations. This enabled the construction of a comprehensive spectral database including spectra from 180 different microbial strains. The FPA-FTIR based method was assessed for the discrimination of Campylobacter jejuni and C. coli isolated from poultry. The method was also evaluated as a tool for the identification of Escherichia coli and Listeria monocytogenes strains isolated from deliberately inoculated food matrices. In all cases identification of bacteria based on their FPA-FTIR spectra was highly reliable and comparable to standard methods of bacteria identification; provided that the unknown bacteria samples and reference strains were prepared in a consistent manner, and that appropriate spectral databases were employed.
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 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 | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".