The PROCESS 2020 Guideline: Updating Consensus Preferred Reporting Of CasE Series in Surgery (PROCESS) Guidelines
Bibliographic record
Abstract
The PROCESS Guidelines were first published in 2016 and were last updated in 2018. They provide a structure for reporting surgical case series in order to increase reporting robustness and transparency, and are used and endorsed by authors, journal editors and reviewers alike. In order to drive forwards reporting quality, they must be kept up to date. As such, we have updated these guidelines via a DELPHI consensus exercise. The updated guidelines were produced via a DELPHI consensus exercise. Members from the previous DELPHI group were again invited, alongside editorial board members and peer reviewers of the International Journal of Surgery and the International Journal of Surgery Case Reports. An online survey was completed by this expert group to indicate their agreement with proposed changes to the checklist items. A total of 53 surgical experts agreed to participate and 49 (92%) completed the survey. The responses and suggested modifications were incorporated into the previous 2018 guidelines. There was a high degree of agreement amongst the PROCESS Group, with all but one of the PROCESS items receiving over 70% of scores ranging 7–9. A DELPHI consensus exercise was completed and an updated and improved PROCESS Checklist is now presented. • This was a DELPHI consensus exercise to update the PROCESS guidelines. • Of the invited surgical experts, 49 (92%) completed the survey. There was a high level of agreement in the PROCESS Group. • The survey responses were incorporated as modifications and an improved PROCESS Checklist is now presented for use.
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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 | 0.272 | 0.511 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.019 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.009 | 0.011 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.008 |
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".