Ants’ Capability of Adding and Subtracting Odors
Bibliographic record
Abstract
Summing and discriminating odors may be useful for animals in their daily life. The workers of the ant Myrmica sabuleti rely essentially on odors for navigating and have a rather poor visual perception. It was previously shown that they can add and subtract visual elements when the result of the operation has been concretely presented to them, i.e. they thus respond to an image which corresponds the best to that they have memorized. Here we examined if these ants can sum two odors and ‘subtract’ (discriminate) an odor from a mixture of two ones. They added two distinct odors only when these odors were presented side by side and perceived simultaneously, and not when they were located at some distance from one another and perceived consecutively. They discriminated one odor from a mixture when that odor was presented in association with a reward (the food). They subtracted one odor from a mixture when that specific odor was presented and perceived separately at a place not associated with a reward. Myrmica sabuleti workers could thus effectively add two odors and subtract one odor from a mixture, but only when the odor(s) to which they should respond was (were) associated with a reward. In the wild, such a behavior could help the ants to navigate.
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 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".