Effects of parasites on host energy expenditure: the resting metabolic rate stalemate
Bibliographic record
Abstract
Detrimental effects of parasitism on host fitness are frequently attributed to parasite-associated perturbations to host energy budgets. It has therefore been widely hypothesized that energetic costs of infection may be manifest as changes in host resting metabolic rate (RMR). Attempts to quantify these effects have yielded contradictory results across host–parasite systems. We used a meta-analysis of the literature to test the effects of parasites on mass-specific (n = 22) and whole-body (n = 15) host RMR. Parasites resulted in a qualitative increase in host RMR in the majority of studies; however, the overall effect of parasites on host RMR was small and statistically nonsignificant. Additionally, substantial among-study variation in host RMR could not be explained by any of the tested covariates. We conclude that the lack of an overall effect of parasites on host metabolism reflects inconsistent directionality and varying magnitudes of parasite-associated effects across studies, rather than an absence of system-specific effects. We contend that a general understanding of parasite effects on host energetics may be best achieved through identifying mechanisms underlying among-system variance in parasite effects on host RMR and relating parasite-associated perturbations of host energy budgets to robust estimates of host fitness.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".