Editorial for issue 4 of 2013, Journal of Evidence Based Medicine
Bibliographic record
Abstract
As 2013 draws to a close, The Cochrane Collaboration is entering its 21st year and we are pleased to be part of those celebrations here at the Journal of Evidence Based Medicine. The recent Cochrane Colloquium saw a gathering of a thousand evidence-based researchers, practitioners and patients from across health and social care in Quebec City, Canada. They were able to look back on the many successes of the Collaboration over its first two decades and anticipate the challenges for the future. More than 31,000 people from over 120 countries are now actively involved in the work of The Cochrane Collaboration. China continues to make a tremendous contribution to this work, with 2700 active participants based in this country. Among these, 2300 are authors on Cochrane Reviews and more than a fifth of them are the contact person for the review. Together, the members of the Collaboration have produced 5500 full Cochrane Reviews over the last 20 years. A further 2300 are at the stage of published protocols. These will be converted to full systematic reviews in the coming years, and be added to by hundreds more. This will maintain the position of the Cochrane Database of Systematic Reviews as the world's largest single repository for the full text of reviews in health and social care. This, coupled with the unique contribution of the Centre for Reviews and Dissemination at the University of York in England which is responsible for DARE, the Database of Abstracts of Reviews of Effects, provides patients, practitioners, policy makers and the public with ready access to the world's systematic reviews, through The Cochrane Library. The driving forces behind Cochrane Reviews are the Cochrane Review Groups, many of whom have published accounts of their work in specialist journals through this year. We are delighted to add to this effort in the current issue of the Journal. You can read articles from a diverse range of Groups, reflecting on their early years and looking to what comes next for them. This future seems set to include greater automation in the review process and Clive Adams, Coordinating Editor of the Cochrane Schizophrenia Group and colleagues, outline a vision for how this might happen elsewhere in this issue.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | no category Domain: not available · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.382 | 0.788 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.020 | 0.006 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.009 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".