EFFECTS OF SPRING BODY CONDITION AND AGE ON REPRODUCTION IN MALLARDS (<i>ANAS PLATYRHYNCHOS</i>)
Bibliographic record
Abstract
We explored predictive models relating body condition and age to nesting propensity, timing of nest initiation, clutch size of first nests, aggregated nest survival, hatching success, and timing of hatch in Mallards (Anas platyrhynchos). Nesting propensity had a positive linear relationship with body condition, and second-year (SY) females had a lower probability of nesting than after-second-year (ASY) females (84% and 94%, respectively, at average body condition). Females in better body condition initiated nesting ∼15 days earlier than those in poor condition, and SY females nested ∼4 days later than ASY females at average body condition. Clutch size of first nests exhibited a curvilinear decline with body condition, such that large clutches were characteristic of females in the best condition that nested early. Nest survival and hatching probability were unaffected by body condition. Younger females had somewhat lower nest survival (11%) than older females (14%), which, in combination with renesting effort, resulted in an age difference in hatching probability (22% and 33%, respectively). Females in better condition hatched nests ∼15 days earlier than those in poor condition, and SY females hatched nests ∼4 days later, on average, than ASY females. Our results indicate that factors influencing the body condition of female Mallards arriving on breeding areas could influence subsequent reproductive investment and success. Condition effects are primarily through the mechanisms of nesting propensity, clutch size, and timing of nest initiation and hatch. Additionally, we provide evidence that Mallards in their first breeding season have lower reproductive potential than older females.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".