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
Most Internet users receive unsolicited invitations to enhance their health through the purchase of online medications. Often these medications are illegal and may even be counterfeit. However, there are a few legitimate online pharmacies. The National Association of Boards of Pharmacy has established the Verified Internet Pharmacy Practice Sites program, which certifies the legitimacy of some Internet merchants. Also, there are hundreds of Canadian pharmacies online because of the rise in popularity of Canadian drugs. The actual number of online Canadian pharmacies is difficult to estimate, and many of the so-called Canadian pharmacies are not from Canada. Besides the few legitimate sites in the United States and Canada, most online pharmacies deal with unapproved, illegal, and counterfeit medication. It is hard to know the number of online pharmacies because of the complex structure of the Internet. Their rapid growth can mainly be attributed to huge profits, but online pharmacies are also used for money laundering and may be used for terrorism. Although the United States has been limited in its actions, it still has taken numerous measures. However, internationally, online pharmacies do not appear to be as much of a problem, so almost any action taken has been led by the United States.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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