A species-specific qPCR assay for the reptile pathogen Nannizziopsis barbatae and mitochondrial genomes of Nannizziopsis and Paranannizziopsis
Bibliographic record
Abstract
Infectious fungal diseases can have devastating effects on wildlife health and our ability to detect emerging fungal pathogens in the wild is considered indispensable for effective management strategies. Several fungi from the genus Nannizziopsis and Paranannizziopsis are emerging pathogens of reptiles and have been observed to cause disease in a wide range of taxa. Nannizziopsis barbatae has become a particularly important pathogen of Australian reptiles with an increasing number of herpetofauna being reported with cases of infection from across the country. Here, we report a species-specific qPCR assay for the rapid detection of N. barbatae and demonstrate its application in a wild urban population of a dragon lizard. In addition, we present the mitochondrial genome sequences and phylogenetic analysis for seven species in this group of fungi to support further research into the evolutionary ecology of these emerging pathogens.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".