Evaluation of a Digestion Assay and Determination of Sample Size and Tissue for the Reliable Detection of <i>Trichinella</i> Larvae in Walrus Meat
Bibliographic record
Abstract
A digestion assay was validated for the detection of Trichinella larvae in walrus (Odobenus rosmarus) meat, and appropriate samples for testing were determined using tissues from infected walruses harvested for food. Examination of muscles from 3 walruses showed that the tongue consistently contained approximately 2-6 times more larvae than the pectoral and intercostal muscles. Comparison of numbers of larvae in the root, body, and apex of the tongue from 3 walruses failed to identify a predilection site within the tongue, but the apex was considered an optimal tissue because of the high larval density within the tongue and the ease of collection. All 31 spiked samples weighing 50 g each and containing between 0.1 and 0.4 larvae per gram (lpg) were correctly identified as infected, indicating that the sensitivity of this procedure is adequate for diagnostic use. A sample size of 10 g consistently detected larvae in 2 walrus tongues containing > or = 0.3 lpg (n = 40), and until additional data are available, sample sizes from individual walrus tongues should be a minimum of 10 g. This study provides the preliminary data that were used for the development of a food safety analytical protocol for the detection of Trichinella in walrus meat in arctic communities.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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".