Bibliographic record
Abstract
The study by Johnson et al. (1) in the December 2002 issue of Diabetes Care makes conclusions that in part seem to support the controversial finding of the U.K. Prospective Diabetes Study (UKPDS) that metformin usage as monotherapy was associated with a lower death rate compared with sulfonylureas or insulin (2,3). Such a claim has huge importance to practitioners and patients. Diabetes incidence and costs (the large bulk of which are attributed to type 2 diabetes) are skyrocketing around the world. The increased cardiovascular (CV) risk with diabetes is well recognized (4), and atherosclerotic heart disease, stroke, peripheral vascular disease, and heart failure account in large part for the excess death rate. The decision about what drug to use for monotherapy is currently based on many factors, such as contraindications, side effects, and cost of the available drugs; our wish to minimize weight gain; the patient’s age and accompanying co-illnesses; the practitioner’s familiarity and comfort level with the various drugs; and perhaps most importantly, what drugs are covered by the patient’s insurance. Efficacy does not play much of a role, as there is little solid evidence for any class of drugs being much different than the rest when used as monotherapy (5). However, showing clinically relevant CV benefits for any of the available drugs would move this decision point to the top of the list. It would be hard to be enthusiastic about another drug irrespective of what other advantages it might have. In their study, Johnson et al. (1) retrospectively surveyed oral agent usage in Saskatchewan from 1 January 1991 to 31 December 1999, looking for “new users,” who were determined based on not having been prescribed an oral hypoglycemic agent in the prior 12 months. The survey used the computerized outpatient prescription drug …
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".