Surveillance for Cryptococcus gattii in horses of Vancouver Island, British Columbia, Canada
Bibliographic record
Abstract
In the last decade Cryptococcus gattii has emerged as an important human and animal pathogen in southwestern British Columbia (BC), Canada. When the disease initially emerged it was identified in humans and multiple animal species on the east coast of Vancouver Island. From fall 2003 until summer 2004, active surveillance was initiated to look for horses exposed to or infected with the organism by performing nasal cultures and serum antigen testing in horses residing within 10 km of known areas of environmental reservoirs of the fungus. Surveillance efforts were facilitated by local equine practitioners who were also encouraged to report clinical cases. Nasal colonization was identified in four of the 260 horses tested but none had a serum cryptococcal antigen titer. All positive horses were from the same geographic area near Duncan, BC. During the study period, a single horse was diagnosed with systemic cryptococcosis and euthanized; clinical and post mortem information is described. As this organism continues to disseminate in the Pacific Northwest it is important for veterinarians to be familiar with the disease as early diagnosis may enable more effective treatment.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".