Establishing the relative importance of sympatric definitive hosts in the transmission of the sealworm, <i>Pseudoterranova decipiens</i>: a host-community approach
Bibliographic record
Abstract
The importance of a given host to a particular parasite can be determined according to three different criteria: host preference, host physiological suitability and host contribution to transmission. Most studies on the sealworm Pseudoterranova decipiens have focussed on the latter factor, but few attempts have been made to develop a quantitative transmission model evaluating the relative importance of each host. The purpose of this study was to propose a flow-chart model to study sealworm transmission within a seal community. The model was applied to hypothetical data of four seal species acting as definitive hosts of P. decipiens sensu stricto in eastern Canada: harp seal Phoca groenlandica, harbour seal P. vitulina, grey seal Halichoerus grypus and hooded seal Cystophora cristata. The dynamics of the model was studied using population estimates from 1990 to 1996. To illustrate the interrelationship of the seal populations in the flow dynamics, the model’s behaviour was explored by manipulation of the harp seal population size. The results showed that grey seals accounted by far for most transmission from and to the seals. The harbour seal population also sustained a biologically significant proportion of the flow, whereas the role of hooded and harp seals seemed negligible despite their large population sizes. The hypothetical removal of the harp seal population resulted in small increases in the relative flows to the other seals. These results conform to previous qualitative assessments on the relative importance of these seal species in sealworm transmission. The model provided some heuristic rules useful to understand transmission patterns. The data suggested that the harbour seal population should be about twice that of the grey seals to account for a larger share of transmission than grey seals. Although this is unlikely to occur at a large geographic scale, harbour seals outnumber grey seals in some areas and, therefore, the role of each host may change locally. To make this approach more realistic, further work should seek accurate estimates of parasite population parameters, better definition of the host community boundaries (at a local scale) and improved control of confounding variables.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".