The effects of egg laying onset, nest size and egg size on the hatching success of the Little Grebe <i>Tachybaptus ruficollis</i>
Bibliographic record
Abstract
In 2008, we investigated the relationships between the hatching success of the Little Grebe Tachybaptus ruficollis with egg laying onset, nest diameter, as a proxy of nest size, and egg weight, as a proxy of egg size, in an artificial wetland in Mazandaran Province, northern Iran. The first egg was laid on April 23 and the last chick hatched on July 27. From 118 eggs on 25 nests, we recorded a total of 72 hatchlings (hatching rate: 61%). A generalized linear model (GLM) revealed that while egg size and nest diameter were not significant factors predicting hatching success, egg laying onset predicted significantly the hatching success as early breeders were likely to produce less hatchlings than late breeders. Further studies will be necessary to elucidate the underlying mechanisms of such results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".