The Adjusting-Paced Serial Addition Test (Adjusting-PSAT): thresholds for speed of information processing as a function of stimulus modality and problem complexity
Bibliographic record
Abstract
A modified computer version of the PASAT (Adjusting-PSAT; Tombaugh, 1999) is described that measures speed of information processing and working memory by means of a temporal threshold rather than number of correct responses. This is accomplished by making the duration of the interval between numbers depend on the correctness of responding—a correct response decreases the interval between digits and an incorrect response increases the interval. Modality of presentation (visual and auditory) was factorially combined with problem difficulty (answers between 2–10 or 2–18). Performance of 60 healthy student volunteers on the Adjusting-PSAT was compared to that obtained on several traditional neuropsychological measures (Digit Span, Trail Making Test, and Symbol Digit Modality Test) and on a test of basic addition skills. The visual version of the test produced a lower threshold than did the auditory version, but problem difficulty did not produce a significant effect. Of the neuropsychological tests, Trails-B (TMT-B) was most highly correlated with thresholds. However, regression analyses revealed that math ability accounted for more variance than did TMT-B. The clinical implications of these finding are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".