Bibliographic record
Abstract
Introduction In many bird species, young beg for care from their parents. A parent arriving at the nest with food is met by begging nestlings, which are waving their wings, calling and stretching to expose brightly coloured gapes, all within the confines of a nest that may contain several other begging nestlings. This mode of parent–offspring communication has become a model for the study of the evolution of biological signalling. Hungrier nestlings beg more intensely, so the parent can use the display to decide which nestling to feed and to decide how soon it should return to the nest with food (reviewed by Budden & Wright, 2001). The fact that the parent can extract information on nestling hunger from such a confusing burst of signalling raises numerous questions. How does each nestling ensure that its own signal of need is received above the din of its nestmates' displays? How do parents differentiate among these displays to choose which nestling to feed? How much do the displays, as opposed to the physical jostling toward the parent that also goes on in the nest, determine which nestlings are fed? To answer such questions we need to understand how the begging behaviours of whole broods function together. Concepts derived from the new field of communication networks seem well suited to this task but have not yet been explicitly applied to begging. As currently defined (McGregor & Dabelsteen, 1996; McGregor & Peake, 2000), a communication network forms whenever several individuals communicate within transmission range of each other's signals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".