A comparison of letter and digit processing in letter-by-letter reading
Bibliographic record
Abstract
The extent to which letter-by-letter reading results from a specific orthographic deficit, as compared with a nonspecific disturbance in basic visuoperceptual mechanisms, is unclear. The current study directly compared processing of letters and digits in a letter-by-letter reader, G.M., using a rapid serial visual presentation (RSVP) task and a speeded matching task. Comparisons were made to a group of six brain-damaged individuals without reading deficits. In the RSVP task, G.M. had increased difficulty reporting the target identities when they were letters, as compared with digits. Although this general pattern was also evident in the control group, the magnitude of the letter-digit accuracy difference was greater in G.M. Similarly, in the matching task, G.M. was slower to match letters than digits, relative to the control group, although his response times to both item types were increased. These data suggest that letter-by-letter reading, at least in this case, results from a visuoperceptual encoding deficit that particularly affects letters, but also extends to processing of digits to a lesser extent. Results are consistent with the notion that a left occipitotemporal area is specialized for letter processing with greater bilaterality in the visual processing 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".