SENSITIVITY OF DOUBLE CENTRIFUGATION SUGAR FECAL FLOTATION FOR DETECTING INTESTINAL HELMINTHS IN COYOTES (CANIS LATRANS)
Bibliographic record
Abstract
Fecal analysis is commonly used to estimate prevalence and intensity of intestinal helminths in wild carnivores, but few studies have assessed the reliability of fecal flotation compared to analysis of intestinal tracts. We investigated sensitivity of the double centrifugation sugar fecal flotation and kappa agreement between fecal flotation and postmortem examination of intestines for helminths of coyotes (Canis latrans). We analyzed 57 coyote carcasses that were collected between October 2010 and March 2011 in the metropolitan area of Calgary and Edmonton, Alberta, Canada. Before analyses, intestines and feces were frozen at -80 C for 72 hr to inactivate Echinococcus eggs, protecting operators from potential exposure. Five species of helminths were found by postmortem examination, including Toxascaris leonina, Uncinaria stenocephala, Ancylostoma caninum, Taenia sp., and Echinococcus multilocularis. Sensitivity of fecal flotation was high (0.84) for detection of T. leonina but low for Taenia sp. (0.27), E. multilocularis (0.46), and U. stenocephala (0.00). Good kappa agreement between techniques was observed only for T. leonine (0.64), for which we detected also a significant correlation between adult female parasite intensity and fecal egg counts (R-s=0.53, P=0.01). Differences in sensitivity may be related to parasite characteristics that affect recovery of eggs on flotation. Fecal parasitologic analyses are highly applicable to study the disease ecology, of urban carnivores, and they often provide important information on environmental contamination and potential of zoonotic risks. However, fecal-based parasitologic surveys should first assess the sensitivity of the techniques to understand their biases and limitations. RI Massolo, Alessandro/I-3437-2012
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".