The relationship between measures of stress and condition in nestling European starlings
Bibliographic record
Abstract
Maintaining an effective immune system is energetically costly.During times of stress, the immune system and an individual's physical condition can become compromised.Elevated white blood cell (WBC) counts, and high heterophil/lymphocyte (H/L; types of WBCs) ratios are two reliable indicators of stress in birds.The objective of this study was to determine whether nestling condition was negatively correlated with stress in European starlings (Sturnus vulgaris).I predicted that nestlings in poor condition would have higher stress and therefore higher overall WBC counts and H/L ratios than nestlings in good condition.The best and worst condition nestlings were chosen from each nest when 14 -15 days of age (n = 16 nests), as measured by regressing mass against tarsus length.Blood smears were made for each of these nestlings with a small blood sample.Smears were then fixed in methanol, stained using Hema III and examined with microscopy to estimate WBC count and H/L ratio per 10,000 erythrocytes.Condition differed significantly between the two nestling groups (best and worst condition).Mean WBC counts per brood tended to be positively correlated with mean H/L ratios per brood.However, counter to my prediction, no correlation existed between mean WBC count and mean nestling condition per brood or mean nestling H/L ratio and mean condition per brood.Differences in H/L ratio, however, were positively correlated with differences in nestling condition, suggesting that nestlings in similar condition are similarly stressed.The lack of significant relationship between H/L ratio and condition found in nestlings contrasts with results from another study done on adult starlings in this same population.Nestlings at 14-15 days of age are likely still developing their immune response, and so WBC counts and H/L ratios are not good measures of stress.
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 | 0.000 | 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".