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
OBJECTIVE: To detect the frequency of potential drug-drug interactions (DDIs) in an outpatient group of elderly people in 6 European countries, as well as to describe differences among countries. DATA SOURCES AND METHODS: Drug use data were collected from 1601 elderly persons living in 6 European countries. The study population participated in a controlled intervention study over 18 months investigating the impact of pharmaceutical care. Potential DDIs were studied using a computerized detection program. RESULTS: The elderly population used on average 7.0 drugs per person; 46% had at least 1 drug combination possibly leading to a DDI. On average, there were 0.83 potential DDIs per person. Almost 10% of the potential DDIs were classified to be avoided according to the Swedish interaction classification system, but nearly one-third of them were to be avoided only for predisposed patients. The risk of subtherapeutic effect as a result of a potential DDI was as common as the risk of adverse reactions. Furthermore, we found differences in the frequency and type of potential DDIs among the countries. CONCLUSIONS: Potential DDIs are common in elderly people using many drugs and are part of a normal drug regimen. Some combinations are likely to have negative effects; more attention must be focused on detecting and monitoring patients using such combinations. As differences in potential DDIs among countries were found, the reasons for this variability need to be explored in further studies.
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 | 0.000 | 0.000 |
| 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) | 0.004 | 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