[Many sources of bias in medical research: experience from systematic reviews].
Bibliographic record
Abstract
A well-conducted systematic review requires a scrupulous assessment of the design of included studies. This may unveil major issues in how studies were planned, conducted and reported. This section presents a few examples. 1) A Cochrane review on pain and sedation management in the newborn identified a study described as a randomized trial, which later, following communication with authors and the editor-in-chief, turned out to be observational. 2) Poor evaluation of heterogeneity and active placebo when pooling studies on inhalation of saline solution for bronchiolitis led to clinical implementation of treatments later shown not to be effective. 3) A Cochrane review on methylphenidate for attention deficit hyperactivity disorder in adults did not identify problems with blinding and a »wash-out« period, resulting in erroneous conclusions. The review was therefore retracted. Although as important as benefits, harms of interventions are often given less attention in trials and 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
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 | 0.657 | 0.838 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.015 | 0.012 |
| Bibliometrics | 0.031 | 0.037 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".