Modern medicine comes online: How putting Wikipedia articles through a medical journal's traditional process can put free, reliable information into as many hands as possible.
Bibliographic record
Abstract
Despite its popularity in medical circles, Wikipedia endures skepticism. Often used to gather information, it is rarely considered accurate or complete enough to guide treatment decisions In the face of this, clinicians and trainees turn to resources like UpToDate with greater frequency and confidence because in clinical medicine, a small error can make a big difference. In this issue of Open Medicine, we've published the first ever formally peer-reviewed, and edited, Wikipedia article. The clinical topic is Dengue Fever. Though there may be a need for shorter, more focused clinical articles published elsewhere as this one expands, it is anticipated that the Wikipedia page on Dengue will be a reference against which all others can be compared. Though it might be decades before we see an end to Dengue, perhaps the end to exhaustive or expensive searches about what yet needs to be done, can bring it sooner.
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 | 0.011 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".