Idiopathic pulmonary fibrosis – clinical management guided by the evidence-based GRADE approach: what arguments can be made against transparency in guideline development?
Bibliographic record
Abstract
Evidence-based guidelines have undergone an incredible transformation over the last number of years. Significant advances include explicit linkages of systematic evidence summaries to the strength and direction of recommendations, consideration of all patient-important factors, transparent reporting of the recommendation generation process including conflict of interest management strategies and the production of clinical practice guidelines which use simple and clear language. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology provides a framework for guideline development and was employed to produce the recently published ATS/ERS/JRS/ALAT update on treatment for idiopathic pulmonary fibrosis (IPF). Herein we discuss the advantages of using an evidence-based approach for guideline development using the IPF process and resultant document as an example.
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 | 0.338 | 0.652 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.013 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".