Supporting self-management: intervention design for those with musculoskeletal conditions in the context of health literacy
Bibliographic record
Abstract
2020 will forever be remembered as the year of the COVID-19 pandemic.For the first time since 1972, the 49th Annual Scientific Meeting of the SAPC, due to be held in Leeds in July 2020, could not take place.The cancellation occurred after the submission deadline for abstracts, and, as there was no capacity for a 'virtual' meeting, these abstracts could not be presented.We thank all of the authors, from around the world, for their submissions, which were, as ever, of high quality, importance, and impact, reflecting the state of our discipline.We have great pleasure in publishing the abstracts in this document.A total of 281 abstracts were submitted, 205 for consideration as 'long orals', and 76 as 'short orals'.A couple of 'technical' points to note: The theme of the meeting was 'Living and Dying Well'.This has become more poignant as the events of 2020 sadly unfold.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.001 |
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".