Knowledge gaps in control of<i>Campylobacter</i>for prevention of campylobacteriosis
Bibliographic record
Abstract
Campylobacteriosis is an important, worldwide public health problem with numerous socio-economic impacts. Since 2015, approximately 230,000 cases have been reported annually in Europe. In the United States, Australia and New Zealand, campylobacteriosis is the most commonly reported disease. Poultry and poultry products are considered important sources of human infections. Poultry meat can become contaminated with Campylobacter during slaughter if live chickens are intestinal carriers. Campylobacter spp. can be transferred from animals to humans through consumption and handling of contaminated food products, with fresh chicken meat being the most commonly implicated food type. Regarding food-borne disease, the most important Campylobacter species are Campylobacter jejuni and Campylobacter coli. In humans, clinical signs of campylobacteriosis include diarrhoea, abdominal pain, fever, headache, nausea and vomiting. Most cases of campylobacteriosis are sporadic and self-limiting, but there are post-infection complications, for example, Guillain-Barrés syndrome. This review summarizes an analysis undertaken by the DISCONTOOLS group of experts on campylobacteriosis. Gaps were identified in: (i) knowledge of true number of infected humans; (ii) mechanisms of pathogenicity to induce infection in humans; (iii) training to prevent transfer of Campylobacter from raw to ready-to-eat food; (iv) development of effective vaccines; (v) understanding transmission routes to broiler flocks; (vi) knowledge of bacteriocins, bacteriophages and antimicrobial peptides as preventive therapies; (vii) ration formulation as an effective preventive measure at a farm level; (viii) development of kits for rapid detection and quantification of Campylobacter in animals and food products; and (ix) development of more effective antimicrobials for treatment of humans infected with Campylobacter. Some of these gaps are relevant worldwide, whereas others are more related to problems encountered with Campylobacter in industrialized countries.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".