Fourier Transform Infrared Spectroscopy for Typing Burkholderia cenocepacia ET12 Isolates
Bibliographic record
Abstract
Respiratory infections due to Burkholderia cenocepacia, particularly the ET12 epidemic strain, are considered sentinel events for persons with cystic fibrosis, as they are often associated with person-to-person transmission and accelerated decline in lung function and early mortality. Current typing methods are generally only available at reference centers, with long turn-around-times, which can affect the identification of outbreaks and critical patient triage. This pilot study aims to add to the growing literature illustrating the potential utility of Fourier transform infrared spectroscopy (FTIR), a novel rapid method, for the successful typing of clinically significant bacteria. In this study, we evaluated its utility to discriminate between the ET12 clone and non-ET12 isolates of B. cenocepacia and compared it to proteomics cluster analysis using MALDI-TOF MS and ClinProTools software. Both methods had encouraging but suboptimal accuracy (≥85% sensitivity and ≥83% specificity), which will likely be improved by extending the spectral region analyzed by the IR Biotyper with updated software.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".