Accelerating Bacterial Identification by Infrared Spectroscopy by Employing Microarray Deposition of Microorganisms
Bibliographic record
Abstract
A microarray method for the deposition of bacteria onto an agar slide was developed to accelerate the formation of microcolonies. Representative microarrays each consisting of 40 micro-spots of five replicates of eight foodborne bacteria (Yersinia enterocolitica, Staphylococcus aureus, Salmonella typhimurium, Listeria monocytogenes, Enterobacter cloacae, Citrobacter freundii, Klebsiella pneumoniae, and Escherichia coli) were printed on a Brain Heart Infusion (BHI) agar slide using a contact micro-spotting robotic system. Within 3 h, sufficient bacterial cells were obtained to allow accurate identification of the microorganism by infrared spectroscopy. This approach allows a "complete-in-a-single-day" analysis of a large array of samples.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".