Errors in pigeons' memory for number: Effects of ITI and DI illumination
Bibliographic record
Abstract
In Experiment 1 all pigeons were trained to discriminate 2 flashes of hopper light in 4 sec from 8 flashes in 4 sec, at a 0 sec delay. One group of pigeons experienced dark lTl’s (Group Dark) while the other experienced an illuminated lTl (Group Light). All birds were then tested with dark delays of 0, 5, 10, 15, and 20 sec. Analysis showed a significant bias to respond to the comparison correct for small at extended delays, with no difference between groups. In Experiment 2 training was identical to that in Experiment l except that a 5 sec baseline delay was used. The pigeons were then tested at delays of 0, 5, 10, 15, and 20 sec. Again, analysis showed a tendency to choose the comparison correct for small at delays longer than baseline, while at delays shorter than baseline they showed a bias to respond large. No group differences were observed. In Experiment 3, an illuminated Dl was introduced for both groups. Analysis showed a reversal of the biases observed in Experiment 2. At delays longer than baseline a choose-large bias occurred, while at delays shorter than baseline a choose-small bias was observed. Again, there were no group differences. It was hypothesized that illuminating the Dl added pulse counts to the pigeons’ memory for the samples, suggesting that an event switch was not being used, but that the total amount of light in each trial was being summed. The results are clearly inconsistent with the contusion hypothesis and support a subjective shortening account of memory biases for temporal discriminations. However, whether this theory can be extended to include a subjective shrinking of number remains in question.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".