Superior abstract-concept learning by Clark's nutcrackers ( <i>Nucifraga columbiana</i> )
Bibliographic record
Abstract
The ability to learn abstract relational concepts is fundamental to higher level cognition. In contrast to item-specific concepts (e.g. pictures containing trees versus pictures containing cars), abstract relational concepts are not bound to particular stimulus features, but instead involve the relationship between stimuli and therefore may be extrapolated to novel stimuli. Previous research investigating the same/different abstract concept has suggested that primates might be specially adapted to extract relations among items and would require fewer exemplars of a rule to learn an abstract concept than non-primate species. We assessed abstract-concept learning in an avian species, Clark's nutcracker (Nucifraga columbiana), using a small number of exemplars (eight pairs of the same rule, and 56 pairs of the different rule) identical to that previously used to compare rhesus monkeys, capuchin monkeys and pigeons. Nutcrackers as a group (N = 9) showed more novel stimulus transfer than any previous species tested with this small number of exemplars. Two nutcrackers showed full concept learning and four more showed transfer considerably above chance performance, indicating partial concept learning. These results show that the Clark's nutcracker, a corvid species well known for its amazing feats of spatial memory, learns the same/different abstract concept better than any non-human species (including non-human primates) yet tested on this same task.
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How this classification was reachedexpand
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".