Update on evidence‐based reviews with recommendations in adult chronic rhinosinusitis
Bibliographic record
Abstract
Chronic rhinosinusitis (CRS) has a significant impact not only on individuals who are afflicted but also on society as a whole. An increasing emphasis is being placed on incorporating the best available evidence into the care of patients, in association with an individual clinician's expertise and the patient's values. Recent evidence-based reviews with recommendations (EBRRs) have distilled our knowledge of CRS treatment options and have also pointed out continued gaps in this knowledge. This review synthesizes the findings of 8 EBRRs regarding CRS published in the International Forum of Allergy and Rhinology between 2011 and 2014. The recommendations in this review are based on the best available evidence and are meant to be incorporated into each patient's individual care, along with the practitioner's expertise and the individual patient's values and expectations. It is hoped that the EBRRs, and the process that spawned them, can provide the foundation for future guidelines in the diagnosis and management of CRS.
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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 | 0.013 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".