Identification of <i>Campylobacter jejuni</i> , <i>C. coli</i> , <i>C. lari</i> , <i>C. upsaliensis</i> , <i>Arcobacter butzleri</i> , and <i>A. butzleri</i> -Like Species Based on the <i>glyA</i> Gene
Bibliographic record
Abstract
Currently, the detection and identification of Campylobacter and Arcobacter species remains arduous, largely due to cross-species phenotypic similarities and a relatively narrow spectrum of biochemical reactivity. We have developed a PCR-hybridization strategy, wherein degenerate primers are used to amplify glyA fragments from samples, which are then subjected to species-specific oligodeoxyribonucleotide probe hybridizations, to identify and distinguish between Campylobacter jejuni, C. coli, C. lari, C. upsaliensis, Arcobacter butzleri, and an A. butzleri-like species. Evaluation of this strategy with genomic DNA from different type strains suggests that this approach is both specific and sensitive and thus may be applicable in a diagnostic assay to identify and differentiate these highly related species.
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 | 0.000 | 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 | 0.000 |
| 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".