Determinants of Host Specificity and Comments on Attachment Site Specificity of Tetraphyllidean Cestodes Infecting Rajid Skates from the Northwest Atlantic
Bibliographic record
Abstract
The objectives of this study were to (1) describe the host range for 6 tetraphyllidean species and quantify their host specificity using 5 specificity indices; (2) determine the role of morphological determinants in the host specificity of tetraphyllideans by comparing villar and bothridial measurements of species examined herein; and (3) determine the role of a physiological component in the host specificity of tetraphyllideans by exposing tetraphyllideans to blood sera from different fish species and other solutions. Our results indicate that Echeneibothrium dubium abyssorum (ex Amblyraja radiata), Echeneibothrium canadensis (ex A. radiata), and Zyxibothrium kamienae (ex Malacoraja senta) exhibit the highest degree of specificity, followed by Echeneibothrium vernetae (ex Leucoraja erinacea and Leucoraja ocellata), Pseudanthobothrium hanseni (ex A. radiata and M. senta), and Pseudanthobothrium purtoni (ex Leucoraja erinacea and L. ocellata). However, these results vary based on the specificity index used. Compatible bothridial and villar measurements indicate that there is no morphological determinant of host specificity but that there is a morphological determinant to attachment site specificity. Our data indicate that attachment site specificity may also be phylogenetically determined. Additionally, the exposure of parasites to blood sera from various hosts confirms that host specificity in this system has a physiological determinant. Therefore, host specificity in this system is determined, at least in part, by physiological factors, whereas attachment site specificity is an extension of host specificity and is phylogenetically determined.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".