Body condition of spring-migrating Green-winged Teal (<i>Anas crecca</i>)
Bibliographic record
Abstract
Spring migration is an energetically demanding event that can impact nutrient dynamics of individuals during the breeding season through carry-over effects. Limited food availability at spring stopover areas may have cross-seasonal effects that adversely impact waterfowl populations. We collected 161 Green-winged Teal (Anas crecca Linnaeus, 1758; hereafter Teal) throughout the Illinois River Valley, USA, during February–April of 2016–2018 and estimated body condition using three condition indices (scaled mass index, scaled wing index, body-size index) for comparison with carcass lipid and protein values. Lipids were 18.3% (95% CI = 1.0%–38.5%) and 21.6% (95% CI = 4.8%–41.0%) greater at locations with moderate (250–600 kg/ha) and high (>600 kg/ha) moist-soil seed densities, respectively, than low moist-seed density (<250 kg/ha) sites. Lipids also increased 2.4% (95% CI = 0.2%–5.1%) with every 10% increase in the proportion of plant seeds in diets and decreased 0.9% (SE = 0.4%–1.4%) and 3.8% (SE = 2.1%–5.4%) with every 1-day increase in collection date and 1 °C rise in mean temperature, respectively. Condition indices based on morphology were poor (r ≤ 0.45) predictors of lipids and led to potentially erroneous conclusions regarding important contributions to body condition. Availability of emergent wetlands with adequate food resources may affect lipid reserves of Teal during spring migration and have cross-seasonal effects during the breeding season.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".