Supplementary Material for: The Spanish GIRO guideline: a paradigm shift in the management of obesity in adults.
Bibliographic record
Abstract
Introduction: Current obesogenic environments, along with intrinsic factors, contribute to the obesity pandemic, which impacts the quality of life and healthcare for individuals with obesity. In addition, discrimination and stigma related to obesity remain widespread in our society. In this scenario, the Spanish Society for the Study of Obesity (SEEDO), in collaboration with 38 recognized scientific societies and 12 patients’ organisation, have elaborated the Spanish guideline for obesity management in adults, referred to as the GIRO guideline. GIRO aims to drive a shift in obesity management and serve as a guide for healthcare professionals (HCPs) to address this chronic and multifactorial disease. Methods: A comprehensive systematic review was conducted and completed with experts’ contribution, with a particular focus on Spanish society. The quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. Experts selected the recommendations and determined their strength through consensus. Results: A total of 121 recommendations were proposed, including 32 adopted from the Canadian Adult Obesity Clinical Practice Guidelines and 89 specific recommendations created for the Spanish context, distributed across five areas of application: 1) Recognition of obesity as a chronic disease; 2) Obesity assessment; 3) Multidisciplinary approach to obesity treatment; 4) Recommendations for obesity management in special populations; and 5) Implementation of the GIRO guideline and future challenges. Conclusion: The GIRO recommendations are intended to serve as a useful and interactive tool for HCPs, policymakers and other stakeholders to ensure access to and quality of healthcare for individuals living with obesity.
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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 | 0.012 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.150 | 0.029 |
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".