Bibliographic record
Abstract
you will find a myriad of interesting articles starting with the one authored by colleagues Adams, Gibson, Lyle, and Strong on an Australian perspective of the development of roles for occupational therapists and physiotherapists in work-related practice.The issue continues with two articles by researchers in Sweden.Svensson and Bj örklund discuss three theoretical perspectives on the rehabilitation of sick-listed people; whereas Hagberg, Vaez, and Alexanderson describe methods for analyzing individual changes in sick-leave diagnoses over time.There are four articles by researchers in Canada.DeLuca and colleagues studied a population of disengaged youths to better understand how to foster resilience in this population of workers.Kramer and colleagues discussed collaborating with intermediary organizations as research partners to help implement workplace health and safety interventions, while Reilly and Tipton use a sub-maximal occupational aerobic fitness test alternative, when a step-test was not appro-priate.Gonc ¸alves and colleagues Lancman, Trudel, Jardim, Sznelwar, Santos, and Freeman provide a noteworthy article on an ergonomic approach to reorganizing parking inspection agents' work productivity, health, and safety in S ão Paulo, Brazil.Also included in this issue are two informative articles from researchers in the United States.Kotowski and Davis investigate the potential short-term relevance of the influence of weight loss on musculoskeletal pain, while Solovieva, Walls, and Dowler conducted a study on a population of individuals with disabilities to better understand the impact of personal assistance services (PAS) on self-care at the workplace.
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 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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.251 | 0.165 |
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".