Author Correction: Dapagliflozin in heart failure with improved ejection fraction: a prespecified analysis of the DELIVER trial
Bibliographic record
Abstract
In the version of this article initially published, there was an error in the abstract, where in the sentence now reading, in part, “In participants with HFimpEF… first worsening heart failure events (HR = 0.84),” the hazard ratio originally read “0.78,” while in the second paragraph of the “Outcomes by HFimpEF status” Results subsection, in the sentence now reading, in part, “The effect of dapagliflozin on HF outcomes was also similar in those with HFimpEF (HR = 0.84, 95% CI = 0.61–1.14) and those with LVEF consistently over 40% (HR = 0.78),” the hazard ratio values were mistakenly interchanged. The values have been updated in the HTML and PDF versions of the article.
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
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 | 0.021 | 0.220 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.077 | 0.025 |
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".