Infectious personalities: behavioural syndromes and disease risk in larval amphibians
Bibliographic record
Abstract
Behavioural consistency or predictability through time and/or different contexts ('syndromes' or 'personality types') is likely to have substantial influence on animal life histories and fitness. Consequently, there is much interest in the forces driving and maintaining various syndromes. Individual host behaviours have been associated with susceptibility to parasitism, yet the role of pre-existing personality types in acquiring infections has not been investigated experimentally. Using a larval amphibian-trematode parasite model system, we report that tadpoles generally showed consistency in their activity level in response to both novel food and parasite exposure. Not only were individual activity level and exploration in the novel food context correlated with each other and with anti-parasite behaviour, all three were significant predictors of host parasite load. This is the first empirical demonstration that host behaviours in other contexts are related to behaviours mitigating infection risk and, ultimately, host parasite load. We suggest that this system illustrates how reliably high levels of activity and exploratory behaviour in different contexts might maximize both energy acquisition and resistance to trematode parasites. Such benefits could drive selection for the behavioural syndrome seen here owing to the life histories and ecological circumstances typical of wood frog (Lithobates sylvaticus) larvae.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".