Bibliographic record
Abstract
It is with honor that we have been selected to serve as Co-Editor-in-Chiefs for the Journal of Aging and Physical Activity (JAPA).As previous Associate Editors for the journal, we have both contributed to JAPA over the past many years by making editorial recommendations and shaping the strategic direction of the journal.We are excited to take on this new role where we will be able to have greater impact for leading the mission of JAPA to disseminate multidisciplinary research on the bi-directional relationship between physical activity and aging.With the growing population of older adults globally and the critical role that physical activity plays in physiological, cognitive, and mental health, as well as quality of life, this research is more important than ever for understanding the aging process and optimizing life and healthspan into our later years.First and foremost, we would like to sincerely thank our predecessor Dr. Samuel Nyman for his leadership over the past three years.During his tenure as Editor-in-Chief, Dr. Nyman significantly advanced the impact of JAPA by adding rigor and best publication standard practices.Among his many accomplishments, he increased the timeliness of reviews which now stand at an average of 54-60 days for first decisions on reviewed articles, improved the process for qualitative research papers by adding a new subsection to the instructions for authors based on the expertise of our qualitative Associate Editors, and introduced a series of high impact Virtual Special Issues with five published so far, the first of which was a collection from the past editors.Collectively, these initiatives have created a better experience for everyone that engages with JAPA, whether as an author or reader, and has promoted the timely publication of top-quality research in the field.We wish Samuel all the best in his new role as Head of the Department of Psychology at the University of Winchester where the impact of his leadership will continue to be appreciated.We would like to take this opportunity to briefly introduce ourselves to the contributors and readers of JAPA.
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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 | 0.017 | 0.074 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.021 | 0.026 |
| Insufficient payload (model declined to judge) | 0.048 | 0.041 |
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".