Bibliographic record
Abstract
Abstract Tools are traditionally defined as objects that are used as an extension of the body and held directly in the hand or mouth. By these standards, a vulture breaking an egg by hitting it with a stone uses a tool, but a gull dropping an egg on a rock does not. This distinction between true and borderline (or proto-tool) cases has been criticized for its arbitrariness and anthropocentrism. We show here that relative size of the neostriatum and whole brain distinguish the true and borderline categories in birds using tools to obtain food or water. From two sources, the specialized literature on tools and an innovation data base gathered in the short note sections of 68 journals in 7 areas of the world, we collected 39 true (e.g. use of probes, hammers, sponges, scoops) and 86 borderline (e.g. bait fishing, battering and dropping on anvils, holding with wedges and skewers) cases of tool use in 104 species from 15 parvorders. True tool users have a larger mean residual brain size (regressed against body weight) than do users of borderline tools, confirming the distinction in the literature. In multiple regressions, residual brain size and residual size of the neostriatum (one of the areas in the avian telencephalon thought to be equivalent to the mammalian neocortex) are the best predictors of true tool use reports per taxon. Innovation rate is the best predictor of borderline tool use distribution. Despite the strong concentration of true tool use cases in Corvida and Passerida, independent constrasts suggest that common ancestry is not responsible for the association between tool use and size of the neostriatum and whole brain. Our results demonstrate that birds are more frequent tool users than usually thought and that the complex cognitive processes involved in tool use may have repeatedly co-evolved with large brains in several orders of birds.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".