Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As a greater proportion of patients survive their initial cardiac insult, medical systems worldwide are being faced with an ever-growing need to understand the mechanisms behind the pathogenesis of chronic heart failure (HF). There is a wealth of information about the role of inflammatory cells and pathways during acute injury and the reparative processes that are subsequently activated. We discuss the different causes that lead to chronic HF development and how the sum of initial inflammatory and reparative responses only sets the trajectory for disease progression. Unfortunately, comparatively little is known about the contribution of the immune system once the trajectory has been set, and chronic HF has been established-which clinically represents the majority of patients. It is known that chronic HF is associated with circulating inflammatory cytokines that can predict clinical outcomes, yet the causative role inflammation plays in disease progression is not well defined, and the majority of clinical trials that target aspects of inflammation in patients with chronic HF have largely been negative. This review will present what is currently known about inflammation in chronic HF in both humans and animal models as a means to highlight the gap in our knowledge base that requires further examination.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it