Flotation techniques (FLOTAC and mini-FLOTAC) for detecting gastrointestinal parasites in howler monkeys
Bibliographic record
Abstract
BACKGROUND: Analyses of environmental correlates of the composition of gastrointestinal parasite communities in black howler monkeys (Alouatta pigra) have been hindered by inadequate calibration techniques of detection and quantification methods of the parasites. Here we calibrate samples and compare the likelihood of parasite detection using two flotation techniques, FLOTAC and Mini-FLOTAC, and compare flotation solution, preservation method and dilution ratio for egg detection and counts of the most common parasites (Controrchis spp. and Trypanoxyuris spp.) in howler monkeys. RESULTS: For samples preserved in 5% formalin, the Mini-FLOTAC technique was the best option for qualitative and quantitative copro-microscopic analysis. This technique displays an 83.3% and 100% detection of Controrchis spp. and Trypanoxyuris spp. infections, respectively. For the trematode Controrchis spp., more eggs per gram of feces (EPG) were recorded with the flotation solution (FS) #7 (zinc sulfate; specific gravity SG = 1.35) at 1:20 and 1:25 dilution than other methods. By contrast, for the nematode Trypanoxyuris spp., the best results were recorded with FS1 (sucrose and formaldehyde; SG = 1.20) at 1:10 dilution. CONCLUSIONS: We recommend the Mini-FLOTAC technique for general use with parasite analysis on frugivore/folivores like the howler monkey, especially if many samples are analyzed. The technique has a high detection rate and the best EPG counts, allowing the qualitative and quantitative analysis of parasite load among the species or populations without the need for specialized equipment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".