Addressing the Differences in Speed of Processing of the Intervening Calculation Task on the Modified Brown-Peterson Task
Bibliographic record
Abstract
The Modified Brown-Peterson task (MBPT) is a task of divided attention and working memory that requires central executive functioning. It is a variant of the Brown-Peterson technique and is useful for studying short-term retention of information. It involves the recall of auditory information under conditions of interference (i.e., counting backwards). Previous research has not addressed the effect of individual differences in processing speed for the intervening calculations. In a sample of 81 young participants, we determined whether the number of correct calculations performed is related to recall performance on the MBPT. Results indicated that the number of calculations performed was not significantly related to the recall performance on the MBPT. Rather, the number of correct calculations performed during the interference task of the MBPT was associated with arithmetic ability as measured by the arithmetic subtest of the Adult Intelligence Scale-III (Wechsler, 1997). These results suggest that the subtractions in the MBPT create interference regardless of mathematical ability or speed at which the subtractions are performed during the interference condition of the MBPT task. This observation suggests that the results on this test are independent of mathematical ability and represent a useful measure of working memory.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".