The Effects of List Difficulty and Modality of Presentation on a Computerized Version of the Paced Serial Addition Test (PSAT)
Bibliographic record
Abstract
The Paced Serial Addition Test (PSAT) presents a series of digits at different speeds with the requirement that the two most recent numbers be added together. Although the PSAT is a relatively difficult test, its level of difficulty may be decreased by changing the number list to make the answers simpler and by presenting the digits visually rather than aurally. In view of this, the present experiment varied both task difficulty (easy vs. hard) and mode of presentation (visual vs. auditory). Task difficulty was manipulated by using two different lists composed of single digits whose answers ranged between 2 and 10 (easy) or 2 and 18 (hard). All stimuli were presented by computer which permitted measurement of response latencies, as well as correctness of responding. The results showed that mode of presentation, but not task difficulty, produced highly significant effects. Additional evidence showed that the ability to compute answers to simple addition problems must be considered as a modulator variable. However, an individual's basic arithmetic ability is not as critical as the modality in which a stimulus is presented. The lower performance associated with the auditory version (i.e., PASAT) was interpreted as an interference effect caused by both the stimulus and the response occurring in a single auditory information processing channel. This interpretation suggests that the PASAT's well documented sensitivity to traumatic brain injury (TBI) may be due, at least in part, to an increased susceptibility to interference effects rather than attributable solely to a decreased rate of information processing.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".