Myrmica sabuleti Workers Cannot Acquire Serial Recognition if not Rewarded
Bibliographic record
Abstract
Having previously found that workers of the ant Myrmica sabuleti can acquire serial recognition when rewarded after having walked a correct visual sequence, we here examined if they can acquire this type of learning (that is recognizing a correct sequence presented together with wrong ones) without being rewarded. Using the same colonies two months later and sequences made of four never previously presented elements, we observed that these ants could not significantly acquire serial recognition. Thereafter, rewarding the ants at each step (element) of the sequence, they could progressively acquire some serial recognition, reaching a score of 60% after seven training days. This score no longer increased the day after, being thus the maximum score the ants could reach. The ant M. sabuleti can thus acquire serial recognition only if duly rewarded during training. Moreover, on the basis of their responses to three wrong sequences during testing, it might be presumed that, when being rewarded at each element of the sequence and not at the end of it, the ants better memorize the first element of the sequence. These studies have demonstrated that ants, particularly the workers of M. sabuleti, can acquire serial recognition only through operant conditioning.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".