Detection of Pathogenic Protozoa in the Diagnostic Laboratory: Result Reproducibility, Specimen Pooling, and Competency Assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stool microscopy as performed in clinical parasitology laboratories is a complex procedure with subjective interpretation. Quality assurance (QA) programs often emphasize proficiency testing as an assessment tool. We describe a result reproducibility assessment tool, which can form part of a broader QA program, and which is based on the blinded resubmission of selected clinical samples, using concordance between the reports of the initial and resubmitted specimen as an indicator. Specimens preserved in sodium acetate-acetic acid-formalin can be stored for several months for use in such a program. The presence of multiple protozoa in one specimen does not affect concordance. Some dilution of specimens occurs in this process, and this may explain poor concordance when specimens with low protozoal concentrations are resubmitted. Evaluation of this tool in a large parasitology laboratory revealed concordance rates for pathogenic protozoa (Entamoeba histolytica/Entamoeba dispar, Giardia lamblia, and Dientamoeba fragilis) of about 80%, which may be considered for use as a benchmark value. We also used this tool to demonstrate that when pairs of specimens from one patient are pooled to create a single specimen, concordance between the results of the individual and pooled specimens is high.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it