Toxoplasma gondii exposure in arctic-nesting geese: A multi-state occupancy framework and comparison of serological assays
Bibliographic record
Abstract
The zoonotic parasite, Toxoplasma gondii, has a worldwide distribution and a cosmopolitan suite of hosts. In arctic tundra regions, the definitive felid hosts are rare to absent and, while the complete transmission routes in such regions have yet to be fully elucidated, trophic and vertical routes are likely to be important. Wild birds are common intermediate hosts of T. gondii, and in the central Canadian arctic, geese are probable vectors of the parasite from temperate latitudes to the arctic regions. Our objective was to estimate seroprevalence of T. gondii in Ross's and Lesser Snow Geese from the Karrak Lake ecosystem in Nunavut, Canada. After harvesting geese by shotgun, we collected blood on filter paper strips and tested the eluate for T. gondii antibodies by indirect fluorescent antibody test (IFAT) and direct agglutination test (DAT). We estimated seroprevalence using a multi-state occupancy model, which reduced bias by accounting for imperfect detection, and compared these estimates to a naïve estimator. Ross's Geese had a 0.39 probability of seropositivity, while for Lesser Snow Geese the probability of positive for T. gondii antibodies was 0.36. IFAT had a higher antibody detection probability than DAT, but IFAT also had a higher probability of yielding ambiguous or unclassifiable results. The results of this study indicate that Ross's Geese and Lesser Snow Geese migrating to the Karrak Lake region of Nunavut are routinely exposed to T. gondii at some point in their lives and that they are likely intermediate hosts of the parasite. Also, we were able to enhance our estimation of T. gondii seroprevalence by using an occupancy approach that accounted for both false-negative and false-positive detections and by using multiple diagnostic tests in the absence of a gold standard serological assay for wild geese.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".