Nest design and the abundance of parasitic<i>Protocalliphora</i>blow flies in two hole-nesting passerines
Bibliographic record
Abstract
:Ectoparasites dwelling in bird nests regularly reduce reproductive success and condition of breeding birds. Thus, establishing the factors that determine the abundance of ectoparasites is important for better understanding of reproductive trade-offs and life history evolution in birds. A recent hypothesis states that interspecific differences in the abundance of ectoparasites may be caused by nest composition. For example, great tits (Parus major) have nests made of mosses and fur, whereas Ficedula flycatchers have nests made of grasses, bast, and bark, and tits are more infested by nest-dwelling ectoparasites than flycatchers. We swapped nests between pairs of great tits and collared flycatchers (F. albicollis) during egg-laying or early incubation and counted parasitic Protocalliphora blow flies at the end of breeding to test this hypothesis experimentally. We controlled statistically for habitat (oak versus spruce forest), brood size, season, year, and mean nestling weight before fledging. We found a significant effect of bird species (tit > flycatcher), habitat (oak > spruce), and year. There was no effect of nest type. Consequently, the hypothesis ascribing the different abundance of ectoparasites in great tits and collared flycatchers to different nest composition was not supported by our study.
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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 | 0.001 |
| 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) | 0.002 | 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".