Epidemiology of NHP-Drug Interactions: Identification and Evaluation
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
Increasing numbers of adults and children around the world are using natural health products (NHPs) to promote wellbeing or alleviate illness. Although often considered safe due to their natural origin, NHPs are potentially pharmacologically active and, therefore may cause harm. Limited data suggest that NHPs can interact with other NHPs as well as with prescription medication and foods. Although some common NHP-drug interactions have been identified and studied, in general, the epidemiology of NHP-drug interactions is not well-understood, in part because these harms are often underreported. Users rarely disclose NHP use to their physicians, and physicians rarely enquire about such use. Even if physicians become aware of a potential NHP-drug interaction, passive surveillance systems mean that it is left to the physician's discretion whether or not to report it to the proper authority. It is likely that active surveillance of NHP-drug interactions would result in increased reporting of NHP-related harms as well as better quality reports. Subsequent lab investigation would determine if adulteration, contamination, species misidentification, or misuse was responsible for the harm, or if a pharmacokinetic or pharmacodynamic NHP-drug interaction occurred. This kind of thorough detection and investigation of potential NHP-drug interactions is necessary to ensure the safe use of NHPs.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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