Supplementary Material for: Obesity in Adults: A 2022 Adapted Clinical Practice Guideline for Ireland
Bibliographic record
Abstract
Background: This Clinical Practice Guideline (CPG) for the management of obesity in adults in Ireland, adapted from the Canadian CPG, defines obesity as a complex chronic disease characterised by excess or dysfunctional adiposity that impairs health. The guideline reflects substantial advances in the understanding of the determinants, pathophysiology, assessment, and treatment of obesity. Summary: It shifts the focus of obesity management toward improving patient-centred health outcomes, functional outcomes, and social and economic participation, rather than weight loss alone. It gives recommendations for care that are underpinned by evidence-based principles of chronic disease management; validate patients’ lived experiences; move beyond simplistic approaches of “eat less, move more” and address the root drivers of obesity. Key Messages: People living with obesity face substantial bias and stigma, which contribute to increased morbidity and mortality independent of body weight. Education is needed for all healthcare professionals in Ireland to address the gap in skills, increase knowledge of evidence-based practice, and eliminate bias and stigma in healthcare settings. We call for people living with obesity in Ireland to have access to evidence-informed care, including medical, medical nutrition therapy, physical activity and physical rehabilitation interventions, psychological interventions, pharmacotherapy, and bariatric surgery. This can be best achieved by resourcing and fully implementing the Model of Care for the Management of Adult Overweight and Obesity. To address health inequalities, we also call for the inclusion of obesity in the Structured Chronic Disease Management Programme and for pharmacotherapy reimbursement, to ensure equal access to treatment based on health-need rather than ability to pay.
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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 | 0.008 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.195 | 0.078 |
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".