Community led lung health support groups: processes, perspectives and roles for researchers
Bibliographic record
Abstract
Extract COPD is a slow-progressing chronic disease characterised by breathing problems, dyspnoea, and exacerbations that have seriously debilitating outcomes [1]. COPD's symptoms impair lung function and lead to increased physical limitations that often result in social isolation [2]. The absence of social networks can lead to developing feelings of isolation and even depression in individuals with COPD [3]. Support groups can provide connection to individuals living with COPD by cultivating peer relationships and a sense of community [4, 5]. Simultaneously, academic partners (researchers) have the expertise to provide support to various health organisations and groups; academics are often skilled at recognising the requirements of a situation and adapting and acting accordingly [6]. As researchers with an active programme of research in lung health and chronic disease management, we recognised the potential value we could lend in working with our local lung health support group.
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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 | 0.161 | 0.156 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.028 | 0.016 |
| Scholarly communication | 0.033 | 0.021 |
| Open science | 0.007 | 0.033 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".