First egg dates for great tits (Parus major) and blue tits (Cyanistes caeruleus) breeding in three deciduous woods in Cambridgeshire, England in 1993 to 2014
Bibliographic record
Abstract
This dataset contains first egg dates for great tits (Parus major) and blue tits (Cyanistes caeruleus) from Monks Wood, Brampton Wood and Wennington Wood in Cambridgeshire, England, over a 22 year period. The dataset runs from the breeding season in 1993 to the end of the breeding season in 2014. The first egg dates are presented as the number of days from the start date which was set as the 1st April each year. Because the timing of breeding of great tits and blue tits is influenced in large part by ambient temperature and the phenology of their main prey, the data were collected as a measure of spring phenology. These data comprise part of a larger long-term study of the influence of habitat (extent, structure and composition) and landscape factors on abundance, distribution and breeding success of woodland birds in English lowland deciduous woodland.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
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".