Cell-mediated immune response affects food intake but not body mass: An experiment with wintering great tits
Bibliographic record
Abstract
:Reduction in body mass is one of the major energetic costs associated with immune challenge. In studies where such findings have been obtained, birds performed their normal activities in a natural environment during the experiments. In such situations food intake after immune challenge was not controlled. Therefore, reduction in body mass could be due to a reduction in foraging activity through difficulties in searching for and finding food. The aim of the present study is to determine whether an immune challenge affects body mass or food intake in wintering great tits maintained in captivity. Ten individuals were kept in an outdoor aviary during the experiments. Cell-mediated immunity was determined by the wing web index using phytohemagglutinin (PHA) injection. Body mass and food intake were measured before and after PHA injection. We found no difference in body mass between pre- and post-PHA injection. However, we found a significant increase in the amount of food intake after PHA injection compared with food intake before injection. Moreover, the magnitude of the immune response, measured by the wing web index, was positively related to the amount of food intake. In conclusion, our results suggest that the immune response to PHA is a costly task for small birds during winter and that this cost is compensated for by the increase in food intake.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".