Developing the RIGHT extension statement for practice guideline protocols: the RIGHT-P statement protocol
Bibliographic record
Abstract
<ns4:p> <ns4:bold>Background</ns4:bold> : A protocol for a practice guideline can facilitate the guideline development process, ensure its transparency, and improve the quality of the guidelines. However, there are currently no reporting guideline for guideline protocols. </ns4:p> <ns4:p> <ns4:bold>Methods</ns4:bold> : We intend to develop an extension of the Reporting Items for Practice Guidelines in HealThcare (RIGHT) statement for guideline protocols (RIGHT-P). We will follow the toolkit for developing a reporting guideline developed by the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) network. We will form a multidisciplinary international team of experts. The development of RIGHT-P will be conducted in 12 steps grouped in three stages over a two-year period. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> The results of RIGHT-P statement will be presented in an article to be published later. </ns4:p> <ns4:p> <ns4:bold>Conclusion</ns4:bold> : This report describes the process of RIGHT-P statement development. We believe RIGHT-P will help guideline developers improve the reporting of guideline protocols and indirectly improve their quality and the quality of guidelines. </ns4:p> <ns4:p> <ns4:bold>Registration</ns4:bold> : We registered the protocol on the <ns4:ext-link xmlns:ns5="http://www.w3.org/1999/xlink" ext-link-type="uri" ns5:href="https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-other-study-designs/#RIGHT-P">EQUATOR network</ns4:ext-link> . </ns4:p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.042 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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; both teacher heads 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".