An Investigation of <i>Bartonella</i> spp., <i>Rickettsia typhi</i> , and Seoul Hantavirus in Rats ( <i>Rattus</i> spp.) from an Inner-City Neighborhood of Vancouver, Canada: Is Pathogen Presence a Reflection of Global and Local Rat Population Structure?
Bibliographic record
Abstract
Urban Norway and black rats (Rattus norvegicus and Rattus rattus) are reservoirs for variety of zoonotic pathogens. Many of these pathogens, including Rickettsia typhi, Bartonella spp., and Seoul hantavirus (SEOV), are thought to be endemic in rat populations worldwide; however, past field research has found these organisms to be absent in certain rat populations. Rats (Rattus spp.) from an inner city neighborhood of Vancouver, Canada, were tested for exposure to and/or infection with SEOV and R. typhi (using serology and PCR), as well as Bartonella spp. (using culture and sequencing). Approximately 25% of 404 rats tested were infected with Bartonella tribocorum, which demonstrated significant geographic clustering within the study area. Infection was associated with both season and sexual maturity. Seroreactivity against R. typhi and SEOV was observed in 0.36% and 1.45% of 553 rats tested, respectively, although PCR screening results for these pathogens were negative, suggesting that they are not endemic in the study population. Overall, these results suggest that the geographic distribution of rat-associated zoonoses, including R. typhi, SEOV, and Bartonella spp., is less ubiquitous than previously appreciated, and is likely dependent on patterns of dispersion and establishment of the rat reservoir host. Further study on global and local Rattus spp. population structures may help to elucidate the ecology of zoonotic organisms in these 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".