Detection of Campylobacter jejuni and Thermophilic Campylobacter spp. from Foods by Polymerase Chain Reaction
Bibliographic record
Abstract
Campylobacter spp. is one of the most commonly reported bacterial causes of acute diarrheal disease in humans throughout the world (1–3). The thermophilic Campylobacter jejuni, C. coli, C. lari, and C. upsaliensis are the most important species, with C. jejuni accounting for more than 95% of all the human Campylobacter infections (4,5). Poultry, raw milk, and water have been implicated as the major vehicles for Campylobacter infection (6,7), although other foods may also become a source of infection through cross-contamination from other food types, a food handler, or a work surface during food preparation (3). Because campylobacters have fastidious growth requirements and relatively inert biochemical characteristics, identification of these organisms and differentiation between species within the genus Campylobacter by cultural methods are time consuming and difficult (8–10). The accuracy of some biochemical tests is also affected by bacterial inoculum size (11), which can be difficult to control. Additionally, Campylobacter cells are usually present in very low numbers and may become injured in foods and environmental water, and therefore become nonculturable (12–15). Because of the foregoing, nucleic acid-based detection methods became alternatives for the detection of campylobacters.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".