Searching for clues for eighteen years: Deciphering the ecological determinants of Cryptococcus gattii on Vancouver Island, British Columbia
Bibliographic record
Abstract
Cryptococcus gattii emerged on Vancouver Island in 1999 for unknown reasons, causing human and animal fatalities and illness. The apparent emergence of this fungus in another temperate area, this time in the Pacific Northwest, suggests the fungus may have expanded its ecological niche. Yet studies that directly examine the potential roles of climatic and land use changes on C. gattii are still lacking. We aim to summarize the existing global literature on the ecology of C. gattii, with particular focus on the gap in knowledge surrounding the potential effects of climatic and land use changes. We systematically reviewed English peer-reviewed literature on the ecological determinants of C. gattii. We included studies published from January 1970 through June 2016 and identified 56 relevant studies for our review. We identified environmental isolations of C. gattii from 18 countries, spanning 72 separate regions across six continents. Fifty-three tree species were associated with C. gattii, spanning 10 climate classifications and 36 terrestrial ecoregions. No studies directly tested the potential effects of climatic changes (including climatic oscillations and global climate change) on C. gattii, while only one study directly assessed those of land use change. To improve model predictions of current and future distributions of C. gattii, more focus is needed on the potential effects of climatic and land use changes to help decrease the public health risk. The apparent emergence of C. gattii in British Columbia is also an opportunity to explore the factors behind emerging infectious diseases in Canada and elsewhere.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".