Visualization of evidence‐based medicine domain knowledge: production and citation of cochrane systematic reviews
Bibliographic record
Abstract
OBJECTIVES: 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. A total 34.7% of CSRs had a cited count of 0, whereas 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 on the same topic. CONCLUSIONS: The capability of CSR production and utilization grew rapidly, but varied among countries and institutions, which was affected by several factors such as the capability of research, resources and the applicability of evidence. It is important to improve evidence translation through educating, training and prioritizing the problems based on real demands of end users.
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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 | MetaresearchBibliometrics Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | BibliometricsScholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.143 | 0.634 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.155 | 0.130 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".