Production and citation of cochrane systematic reviews: a bibliometrics analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the production and utilization of Cochrane systematic reviews(CSRs) and to analyze its influential factors, so as to improve the capacity of translating CSRs into practice. METHODS: All CSRs and protocols were retrieved from the Cochrane Library ISSUE 2, 2011 and citation data were retrieved from SCI database. Citation analysis was used to analyze the situation of CSRs production and utilization. RESULTS: CSR publication had grown from an annual average of 32 to 718 documents. Only one developing country was among the ten countries with the largest amount of publications. High income countries accounted for 83% of CSR publications and 90.8% of cited counts. 34.7% of CSRs had a cited count of 0, while only 0.9% had been cited more than 50 times. Highly cited CSRs were published in England, Australia, Canada, USA and other high income countries. The countries with a Cochrane center or a Cochrane methodology group had a greater capability of CSRs production and citing than others. The CSRs addressing the topics of diseases were more than those targeted at public health issues. There was a big gap in citations of different interventions even for the same topic. CONCLUSION: The capability of CSR production and translation grew rapidly, but varied among countries and institutions, which was affected by several factors such as the capability of research, the resourcesand the applicability of the evidence. It is important to improve evidence translation through educating, training and prioritizing the problems based on real demands of end user. This article is protected by copyright. All rights reserved.
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.
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 | 0.407 | 0.734 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.019 | 0.041 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it