Left to Right Oriented Number Scaling in an Ant
Bibliographic record
Abstract
Trained to a smaller number of elements versus a larger one and then tested faced with the larger number and twice the smaller one, one set on the left and the other on the right of the larger number, the ants essentially reacted to the smaller number located on the left of the larger one. Trained to a larger number of elements versus a smaller one and then tested faced with the smaller number and twice the larger one, one set on the left and the other on the right of the smaller number, the ants went preferentially to the larger number located on the right of the smaller one. They similarly reacted when trained to zero versus 2 elements (mostly reacting to the zero element located on the left of the 2 elements), and when trained to 2 elements versus zero element (going essentially to the 2 elements located on the right of the zero element). Thus, the ants responded mostly to the left smaller and the right larger number of elements, and this only when a larger and a smaller respectively number of element was set in the middle. In the absence of the latter, the ants went equally to the left and the right numbers of elements. The ants arrange thus mentally the numbers (amounts) on a scale, a number line, locating the smaller quantities on the left and the larger ones on the right, as do humans and the vertebrates which have already been studied as for this numerosity characteristic. Also, the ants’ accuracy of response decreases with increasing numbers of elements.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".