The Contribution of Handsearching European General Health Care Journals to the Cochrane Controlled Trials Register
Bibliographic record
Abstract
A fundamental aim of any systematic review is that all relevant studies should be identified and considered for inclusion. Limitations with searching bibliographic databases led the Cochrane Collaboration to search journals by hand for reports of trials. This article presents the results of a 3-year project to identify and make accessible reports of randomized trials published in European general health care journals. Overall, 21,620 reports of controlled trials were identified from 119 journals from 16 countries. More than three quarters (76%) were published in U.K. or German journals. Only 3,640 (17%) reports were indexed in MEDLINE as controlled trials, and 6,554 (30%) were not indexed in MEDLINE at all. Bibliographic details for all reports are available by searching The Cochrane Controlled Trials Register in The Cochrane Library. This project has ensured that a large proportion of trial reports not previously identifiable has been made accessible to those preparing systematic reviews.
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 | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.680 | 0.924 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.018 | 0.008 |
| Bibliometrics | 0.102 | 0.082 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.021 | 0.030 |
| Open science | 0.010 | 0.020 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".