From a sequential pattern, temporal adjustments emerge in hummingbird traplining
Bibliographic record
Abstract
Animals that feed from resources that are constant in space and that refill may benefit from repeating the order in which they visit locations. This is a behavior known as traplining, a spatial phenomenon. Hummingbirds, like other central-place foragers, use short traplines when moving between several rewarding sites. Here we investigated whether traplining hummingbirds also use relevant temporal information when choosing which flowers to visit. Wild rufous hummingbirds that were allowed to visit 3 artificial flower patches in which flowers were refilled 20 min after they had been depleted repeated the order in which they visited the 3 patches. Although they tended to visit the first 2 patches sooner than 20 min, they visited the third patch at approximately 20-min intervals. The time between visits to the patches increased across the experiment, suggesting that the birds learned to wait longer before visiting a patch. The birds appeared to couple the sequential pattern of a trapline with temporal regularity, to some degree. This suggests that there is a temporal component to the repeated spatial movements flown by foraging wild hummingbirds.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".