Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Working memory (WM) training explores whether and how repeated practice on working memory tasks might generalize to a variety of outcome measures. Although this field of research is part of the growing literature in cognitive sciences, it has spawned contentious debates. The controversies are largely driven by inconsistent findings and commercial interests, and as a result, numerous meta-analyses and systematic reviews have focused on the validity of WM training. Similarly, there is an inconsistency in the conclusions drawn by these meta-analyses; while there seems to be an agreement about the generalization to proximal cognitive measures; there is a discrepancy in the interpretation of any translational outcomes (e.g., behavioral, clinical, and academic). In this chapter, we review the collection of meta-analyses with a particular focus on children diagnosed with ADHD and other developmental disabilities, and recommend that the field should focus on improving our understanding of the mechanistic and effectiveness properties of WM training, which might result in the development of valuable alternative and/or supplemental approaches, when traditional interventions might fall short, especially for individuals typically underrepresented and underserved.
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.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it