Comparative genomic fingerprinting of <i>Campylobacter</i>: application in routine public health surveillance and epidemiological investigations
Bibliographic record
Abstract
A subtyping methodology for Campylobacter, Comparative Genomic Fingerprinting (CGF40), has been described recently. The objective of this study was to assess the utility of CGF40 as a tool to enhance routine public health surveillance of campylobacteriosis. Isolates of Campylobacter from across the province were requested and sent for CGF40 subtyping. Epidemiological data from cases reported to public health officials in Nova Scotia, Canada, from January 2012 to March 2015 were linked with blinded CGF40 subtyping results. CGF40 was epidemiologically valid; subtyping discerned known epidemiologically related isolates and augmented case-finding. Predominant sources and locations of subtype detection from the national reference database showed some study subtypes were rare and even novel to the database, while others were more commonly identified over multiple years and with exposures locally and internationally. A case-case study design was applied to examine risk factors for the most common CGF40 subtypes detected. Differences in the epidemiology of different CGF40 subtypes were observed. Statistically significant associations were noted for specific subtypes with rural residence, local exposure, contact with a pet dog or cat, contact with chickens, and drinking unpasteurized milk. With prospective use, CGF40 could potentially identify unrecognized outbreaks and contribute to epidemiological investigations of case clusters.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".