Comparison of methods for the concentration of<i>Cryptosporidium</i>oocysts and<i>Giardia</i>cysts from raw waters
Bibliographic record
Abstract
This study compared the recovery of Cryptosporidium oocysts and Giardia cysts ((oo)cysts) from raw waters using 4 different concentration-elution methods: flatbed membranes, FiltaMax foam, Envirochek HV capsules, and Hemoflow ultrafilters. The recovery efficiency of the combined immunomagnetic separation and staining steps was also determined. Analysis of variance of arcsine-transformed data demonstrated that recovery of Cryptosporidium oocysts by 2 of the methods was statistically equivalent (flatbed filtration 26.7% and Hemoflow 28.3%), with FiltaMax and Envirochek HV recoveries significantly lower (18.9% and 18.4%). Recovery of Giardia cysts was significantly higher using flatbed membrane filtration (42.2%) compared with the other 3 methods (Envirochek HV 29.3%, FiltaMax 29.0%, and Hemoflow 20.9%). All methods were generally acceptable and are suitable for laboratory use; 2 of the methods are also suitable for field use (FiltaMax and Envirochek HV). In conclusion, with recoveries generally being statistically equivalent or similar, practical considerations become important in determining which filters to use for particular circumstances. The results indicate that while low-turbidity or "finished" waters can be processed with consistently high recovery efficiencies, recoveries from raw water samples differ significantly with variations in raw water quality. The use of an internal control with each raw water sample is therefore highly recommended.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".