Valsartan is more effective than placebo in reducing the incidence of diabetes in people with impaired glucose tolerance and cardiovascular disease or risk factors but has no effect on cardiovascular outcomes: Table 1
Bibliographic record
Abstract
Commentary on: McMurray JJ, Holman RR, Haffner SM, et al.; NAVIGATOR Study Group. Effect of valsartan on the incidence of diabetes and cardiovascular events. N Engl J Med 2010;362:1477–90[OpenUrl][1][CrossRef][2][PubMed][3]. Impaired glucose tolerance, which represents an intermediate stage before the onset of diabetes, is associated with an increased risk of cardiovascular diseases. Moreover, the concomitant presence of confirmed cardiovascular disease or cardiovascular risk factors in glucose-intolerant patients significantly augments their risk of cardiovascular events. Among the different treatment strategies used in high-risk patients, blockade of the renin-angiotensin system (RAS) has been shown to decrease the onset of new diabetes as well as the incidence of cardiovascular events. Therefore, the NAVIGATOR study was designed to evaluate the efficacy of blocking the RAS on the incidence of predetermined cardiovascular events such as myocardial infarction and stroke and on the prevalence of new diabetes. This was a double-blind, randomised, placebo-controlled, clinical trial (ClinicalTrials.gov … [1]: {openurl}?query=rft.jtitle%253DN%2BEngl%2BJ%2BMed%26rft_id%253Dinfo%253Adoi%252F10.1056%252FNEJMoa1001121%26rft_id%253Dinfo%253Apmid%252F20228403%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1056/NEJMoa1001121&link_type=DOI [3]: /lookup/external-ref?access_num=20228403&link_type=MED&atom=%2Febmed%2F16%2F4%2F122.atom
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".