Bibliographic record
Abstract
Aiming to define the ants’ cognitive abilities, we examined if they could learn a correct sequence and recognize it among others made of the same elements but otherwise ordered. We first trained them to a sequence of three elements. They could recognize the correct sequence from the two wrong sequences, reaching a score of 66.9% after 8 training days, what was a rather low though statistically significant score. When trained to a sequence of 4 elements, the ants could also recognize the correct sequence from three wrong ones, reaching the low though statistically significant score of 51.2% in 8 training days. In this second experiment, the ants appeared to better learn the two last elements of the sequence (those directly associated with the reward) than the two first ones. This was in agreement with our previous finding that ants could learn a behavioral sequence only if trained according to a backwards chaining, i.e. if firstly presented with the element associated to the reward. Such kind of learning is in fact some operant conditioning, and apparently differs from what occurs in vertebrates since the latter learn a behavioral sequence under a backward as well as a forward method, and better remember not only the last but also the first element of a series. The neural mechanism(s) underlying serial recognition may thus at least partly differ between vertebrates and invertebrates.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".