Population growth of<i>Gyrodactylus kobayashii</i>in goldfish (<i>Carassius auratus</i>) associated with host density
Bibliographic record
Abstract
Abstract Host density is a key regulatory factor in parasite transmission. The goldfish (Carassius auratus)-Gyrodactylus kobayashiimodel was used to investigate effects of host density on population growth of gyrodactylids. A donor fish infected by five gravid gyrodactylids was mixed with 11 parasite-free goldfish at five host densities. There was a significant positive correlation between host density and mean abundance ofG. kobayashiithroughout the 58-day experiment. During early infection (days 15–24), mean abundance in medium high (0.5 fish L−1) and high host density groups (1 and 2 fish L−1) was significantly higher than that in the low host density groups (0.125 and 0.25 fish L−1). At high host density, prevalence increased more rapidly, and the peak prevalence was higher. Fitting of an exponential growth model showed that the population growth rate of the parasite increased with host density. A hypothesis was proposed that higher host density contributed to increased reinfection of detached gyrodactylids. A reinfection experiment was designed to test this hypothesis. Both mean abundance and prevalence at a host density of 1 fish L−1were significantly higher than those at 0.25 fish L−1on days 1 and 3, which suggested that more reinfections ofG. kobyashiioccurred at the higher host density. Density-dependent transmission during the early infection was an important contributor of population growth ofG. kobayashii, as well as density-dependent reinfection of the detached gyrodactylids.
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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".