Association, in an Ant, of a Quantity of an Element with the Time Period of Its Learning
Bibliographic record
Abstract
The workers of the ant Myrmica sabuleti detain numerosity abilities, have a notion of the running time, and can acquire operant conditioning. The present work examines if, according to these skills and through conditioning, the workers of this ant can associate a learned quantity of a given element with the time period of its occurrence. We collectively trained such ants from 8 to 19 o’clock to a stand bearing a given quantity of an element and from 20 o’clock to 7 o’clock next day to a stand bearing another quantity of the same element, and we tested them in front of these two amounts at 16 o’clock and 4 o’clock next day. At 16 o’clock, the ants reacted essentially to the amount presented during training from 8 to 19 o’clock, and at 4 o’clock to the amount presented during training from 20 o’clock to 7 o’clock. They thus associated the learned quantity of an element with the period of the day during which this learning occurred. It may be argued that this association simply results from the three cognitive capabilities cited here above, and does not require any other more complex skill. In addition, the ants appeared to have better learned from 20 to 7 o’clock than from 8 to 19 o’clock, i.e., during the time of day corresponding to their period of highest natural activity.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".