PRIASE 2021 guidelines for reporting animal studies in Endodontology: a consensus‐based development
Bibliographic record
Abstract
Animal testing is crucial in situations when research on humans is not allowed because of unknown health risks and ethical concerns. The current project aims to develop reporting guidelines exclusively for animal studies in Endodontology, using an established consensus-based methodology. The guidelines have been named: Preferred Reporting Items for Animal Studies in Endodontology (PRIASE) 2021. Nine individuals (PD, VN, AK, PM, MN, JF, EP, JJ and SJ), including the project leaders (PD, VN) formed a steering committee. The steering committee developed a novel checklist by adapting and integrating their animal testing and peer review experience with the Animals in Research: Reporting In Vivo Experiments (ARRIVE) guidelines and also the Clinical and Laboratory Images in Publications (CLIP) principles. A PRIASE Delphi Group (PDG) and PRIASE Online Meeting Group (POMG) were also formed. Thirty-one PDG members participated in the online Delphi process and achieved consensus on the checklist items and flowchart that were used to formulate the PRIASE guidelines. The novel PRIASE 2021 guidelines were discussed with the POMG on 9 September 2020 via a Zoom online video call attended by 21 individuals from across the globe and seven steering committee members. Following the discussions, the guidelines were modified and then piloted by several authors whilst writing a manuscript involving research on animals. The PRIASE 2021 guidelines are a checklist consisting of 11 domains and 43 individual items together with a flowchart. The PRIASE 2021 guidelines are focused on improving the methodological principles, reproducibility and quality of animal studies in order to enhance their reliability as well as repeatability to estimate the effects of endodontic treatments and usefulness for guiding future clinical studies on humans.
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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 | 0.370 | 0.464 |
| Meta-epidemiology (narrow) | 0.002 | 0.005 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.010 | 0.011 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.027 | 0.032 |
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".