Visuospatial cues for reinstating mental models in working memory during interrupted reading.
Bibliographic record
Abstract
Reading involves constructing a mental representation in long-term working memory of the world described by the text. Disrupting short-term working memory can interfere with the maintenance of mental models (sets of retrieval cues) needed to access these representations, producing detrimental effects on reading time. In two experiments, subjects read passages that included pairs of coreferential sentences interrupted by unrelated text. As in previous research, reading times increased for the first sentence after the interruption, likely reflecting a reinstatement process for mental models in working memory. In the present research, pictures were provided as visuospatial cues to aid the reinstatement process. The interruption effect was found to be smaller with pictures related to the passages than with unrelated pictures (Experiment 1) or titles (Experiment 2); however, both of these effects occurred only for slow readers. The authors hypothesize that slow readers take the time needed to integrate visuospatial information into their mental models, providing more resilient access to long-term 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 | 0.000 | 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 | 0.000 |
| 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".