Bibliographic record
Abstract
We describe a case study of C, an alphanumeric-colour synaesthete, who has an extraordinary memory for digits. When C views a black digit, it elicits a highly specific colour (i.e., photism) that is experienced as an overlay which conforms to the shape of the digit. In an initial experiment, we evaluated how C's synaesthetic photisms influence her immediate and delayed recall of digits. C and seven non-synaesthetes were presented with three matrices of 50 digits. One matrix consisted of black digits, and two matrices consisted of colored digits. One matrix of colored digits contained digits that were colored to be congruent with C's photisms for the digits, whereas the other matrix of colored digits contained digits that were colored to be incongruent with C's photisms for the digits. The results showed that C's immediate recall of the incongruently colored digits was considerably poorer than her recall of either the black or the congruently colored digits. Similar differences in the recall of the digits from the three matrices were not shown by any of the seven non-synaesthetes. Furthermore, when immediate and delayed (48 hours) recall of the black digits was compared, C showed no decrease in recall over time, whereas each of the non-synaesthetes showed a significant decrease in recall over time. In a subsequent experiment, we sought to rule out the possibility that C's superior delayed recall of the black digits simply reflected a general, above average memory ability. In this experiment, C and seven non-synaesthetes were presented with matrices of shapes that do not elicit color experiences for C. The results showed that unlike her superior delayed recall of black digits, C's delayed recall of shapes was no different than the delayed recall of the non-synaesthetes. Taken together, the findings clearly demonstrate C's extraordinary memory for digits and show that C's synaesthetic photisms influence her immediate and delayed recall of digits.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".