Yeast microbiota of natural cavities of manatees (<i>Trichechus inunguis</i> and <i>Trichechus manatus</i>) in Brazil and its relevance for animal health and management in captivity
Bibliographic record
Abstract
The aim of this study was to characterize the yeast microbiota of natural cavities of manatees kept in captivity in Brazil. Sterile swabs from the oral cavity, nostrils, genital opening, and rectum of 50 Trichechus inunguis and 26 Trichechus manatus were collected. The samples were plated on Sabouraud agar with chloramphenicol and incubated at 25 °C for 5 days. The yeasts isolated were phenotypically identified by biochemical and micromorphological tests. Overall, 141 strains were isolated, of which 112 were from T. inunguis (Candida albicans, Candida parapsilosis sensu stricto, Candida orthopsilosis, Candida metapsilosis, Candida guilliermondii, Candida pelliculosa, Candida tropicalis, Candida glabrata, Candida famata, Candida krusei, Candida norvegensis, Candida ciferri, Trichosporon sp., Rhodotorula sp., Cryptococcus laurentii) and 29 were from T. manatus (C. albicans, C. tropicalis, C. famata, C. guilliermondii, C. krusei, Rhodotorula sp., Rhodotorula mucilaginosa, Rhodotorula minuta, Trichosporon sp.). This was the first systematic study to investigate the importance of yeasts as components of the microbiota of sirenians, demonstrating the presence of potentially pathogenic species, which highlights the importance of maintaining adequate artificial conditions for the health of captive manatees.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".