Predictors of incubation costs in seabirds: an evolutionary perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Energy costs during breeding play an important role in the evolution of life history traits. Seabirds show substantial variation in both incubation shift length ( ISL ) and metabolic rates. However, it is still unclear how variation in life history traits relates to incubation metabolic rates ( IMR ). Here, we examine the relationship between IMR and life history traits, including ISL , fledging strategy (precocial to altricial), incubation period, nest location (surface vs. underground) and clutch mass relative to adult body mass for 30 species of seabirds collated from the literature. Using both conventional non‐phylogenetic and phylogenetic generalized least‐squares approaches, we show that IMR is negatively associated with ISL , relative clutch mass and with underground nesting, while fledging strategy and incubation period have no impact on IMR once phylogeny is accounted for. Maximum likelihood reconstructions further suggest than ancestral seabirds had average ISL and relative clutch mass, and were surface nesters. We conclude that lower metabolic rates during incubation are associated with both an increased incubation shift length that allows animals to travel farther, as well as the evolutionary emergence of underground nesting that requires less social interaction.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it