Bibliographic record
Abstract
Heart Failure NewsThis issue sees the start of a new section, Heart Failure News.This new section aims at having articles about new findings as well as people and institutions who have a major role in the knowledge and treatment of heart failure (HF).It will show the 'human aspect' of HF care and research.Andrew Coats, President-Elect of the Heart Failure Association (HFA), has the role to take care of these articles. Eplerenone and renal function in EMPHASIS-HFFerreira et al. 9 examined the effect of different eplerenone doses based on pre-specified renal function stratification in the Eplerenone in Mild Patients Hospitalization and Survival Study in HF (EMPHASIS-HF).The target dose of eplerenone/placebo was stratified at randomization to 50 mg/day if estimated glomerular filtration rate (eGFR) was ≥ 50 mL/min/1.73m 2 and ≤ 25 mg/day if eGFR was 30-49 mL/min/1.73m 2 .Renal function had no impact on the efficacy of eplerenone vs. placebo.However, despite
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 | 0.011 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.118 | 0.042 |
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".