How Do Migratory Species Stay Healthy Over the Annual Cycle? A Conceptual Model for Immune Function and For Resistance to Disease
Bibliographic record
Abstract
Migration has fascinated researchers for years and many active areas of study exist. However, the question of how migratory species stay healthy within the context of their annual cycle remains relatively unexplored. This article addresses this question using Red Knots (Calidris canutus) as a model migrant species. We review recent research on immune function in Red Knots and integrate this work with the broader eco-immunological literature to introduce a conceptual model. This model synthesizes earlier ideas about resource allocation and the costs of immunity with recent increases in our knowledge about the vertebrate immune system and then puts these concepts into the context of defense against real pathogens in environments where a myriad of factors change in time and space. We also suggest avenues for further research, which will help to test the model and better link measures of immune function to pressure from pathogens and to optimal defense against disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".