Preparing for a Bsal invasion into North America has improved multi-sector readiness
Bibliographic record
Abstract
Western palearctic salamander susceptibility to the skin disease caused by the amphibian chytrid fungus Batrachochytrium salamandrivorans (Bsal) was recognized in 2014, eliciting concerns for a potential novel wave of amphibian declines following the B. dendrobatidis (Bd) chytridiomycosis global pandemic. Although Bsal had not been detected in North America, initial experimental trials supported the heightened susceptibility of caudate amphibians to Bsal chytridiomycosis, recognizing the critical threat this pathogen poses to the North American salamander biodiversity hotspot. Here, we take stock of 10 years of research, collaboration, engagement, and outreach by the North American Bsal Task Force. We summarize main knowledge and conservation actions to both forestall and respond to Bsal invasion into North America. We address the questions: what have we learned; what are current challenges; and are we ready for a more effective reaction to Bsal’s eventual detection? We expect that the many contributions to preemptive planning accrued over the past decade will pay dividends in amphibian conservation effectiveness and can inform future responses to other novel wildlife diseases and extreme threats.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".