Engaging northern communities in monitoring traditional country foods for zoonotic anisakid nematodes
Bibliographic record
Abstract
This thesis investigated the potential for human health impacts of zoonotic anisakid nematode infections in Inuit-caught fish and marine mammals from Nunavik and Nunatsiavut, Canada, from July 2007 to August 2009. Anisakids were found in seven of eight fish species and two of three marine mammal species tested. Potential risk factors affecting parasite abundance were investigated using negative binomial models. Length was most commonly statistically significant; within species longer animals had greater parasite abundances. The potential for human infection prompted community-based qualitative investigations into perceptions of Inuit residents of Nain (Nunatsiavut) on country foods and strategies for dissemination of research results. Nain residents described the importance of country foods and concerns regarding the safety and security of these foods. Participants stressed the necessity of visual and interactive methods to present research results. Study findings can thus be used to inform Inuit about the animals that pose the greatest risk for infection with zoonotic anisakids.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".