Use of Thiazolidinediones and Risk of Heart Failure in People With Type 2 Diabetes: A Retrospective Cohort Study
Bibliographic record
Abstract
We thank Karter et al. (1) for their comments regarding our study (2). We agree that its principal weakness is the possibility of residual confounding, and we acknowledge this limitation in our article. We also agree that comparison of patients initiating thiazolidinediones (TZDs) with all those receiving other oral antidiabetic agents (new starters plus those on maintenance therapy) may have biased our findings against TZDs. On the other hand, the alternative of comparing patients initiating therapy with TZDs with those initiating other oral antidiabetic agents could have imparted a potentially more serious bias to the study because (as Karter et al. note) the former may be more likely to be initiated later in the course of the disease than the latter. Lacking data on the duration of diabetes, we chose an approach that we hoped would …
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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, 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".