Referee report. For: Multidrug-resistant Campylobacter jejuni, Campylobacter coli and Campylobacter lari isolated from asymptomatic school-going children in Kibera slum, Kenya [version 1; peer review: 2 approved with reservations]
Bibliographic record
Abstract
Background: The objective of this study was to determine the prevalence of thermophilic Campylobacter spp. in asymptomatic school-going children and establish the antibiotic resistant patterns of the isolates towards the drugs used to treat campylobacteriosis, including macrolides, quinolones and tetracycline. Campylobacter spp. are a leading cause of enteric illness and have only recently shown resistant to antibiotics. Methods: This study isolated Campylobacter spp., including Campylobacter coli , Campylobacter jejuni and Campylobacter lari , in stool samples from asymptomatic school-going children in one of the biggest urban slums in Kenya. The disc diffusion method using EUCAST breakpoints was used to identify antibiotic-resistant isolates, which were further tested for genes encoding for tetracycline resistances using primer-specific polymerase chain reaction. Results: In total, 580 stool samples were collected from 11 primary schools considering both gender and age. Subjecting 294 biochemically characterized Campylobacter spp. isolates to genus-specific PCR, 106 (18.27% of stool samples) isolates were confirmed Campylobacter spp. Out of the 106 isolates, 28 (4.83%) were Campylobacter coli , 44 (7.58%) were Campylobacter jejuni while 11 (1.89%) were Campylobacter lari . Campylobacter jejuni had the highest number of isolates that were multi-drug resistant, with 26 out of the 28 tested isolates being resistant to ciprofloxacin (5 mg), nalidixic acid (30 mg), tetracycline (30 mg) and erythromycin (15 mg). Conclusions: In conclusion, a one-health approach, which considers overlaps in environment, animals and human ecosystems, is recommended in addressing campylobacteriosis in humans, since animals are the main reservoirs and environmental contamination is evident.
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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 | 0.002 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.365 | 0.121 |
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".