Methods for living evidence synthesis: a systematic review protocol
Bibliographic record
Abstract
Background : Living evidence (LE) refers to the methodological process that permits new research findings to be continually incorporated to evidence synthesis as they become available. This approach is of great value in the resolution of relevant and rapidly changing clinical questions. To date, the methods to carry out this type of synthesis are not completely defined, and great variability is observed in the approaches used by different groups of authors. Objective: To identify and summarise the current methods used for living evidence synthesis. Methods: We will conduct a systematic literature review of systematic reviews, overviews, and network metanalyses that have used “living evidence synthesis” as part of their methods. The search will be conducted in Medline (via PubMed) and the Epistemonikos database. Two reviewers will independently screen each article for eligibility, extract data, and assess the methodological quality standards of the study accordingly. This protocol is being registered in Prospero.
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 | 0.240 | 0.331 |
| Meta-epidemiology (narrow) | 0.007 | 0.010 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.212 | 0.055 |
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".