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
The progression from cardiac injury to symptomatic heart failure has been intensely studied over the last decade, and is largely attributable to a loss of functional cardiac myocytes through necrosis, intrinsic and extrinsic apoptosis pathways and autophagy. Therefore, the molecular regulation of these cellular programs has been rigorously investigated in the hopes of identifying a potential cell target that could promote cell survival and/or inhibit cell death to avert, or at least prolong, the degeneration toward symptomatic heart failure. The nuclear factor (NF)-κB super family of transcription factors has been implicated in the regulation of immune cell maturation, cell survival, and inflammation in many cell types, including cardiac myocytes. Recent studies have shown that NF-κB is cardioprotective during acute hypoxia and reperfusion injury. However, prolonged activation of NF-κB appears to be detrimental and promotes heart failure by eliciting signals that trigger chronic inflammation through enhanced elaboration of cytokines including tumor necrosis factor α, interleukin-1, and interleukin-6, leading to endoplasmic reticulum stress responses and cell death. The underlying mechanisms that account for the multifaceted and differential outcomes of NF-κB on cardiac cell fate are presently unknown. Herein, we posit a novel paradigm in which the timing, duration of activation, and cellular context may explain mechanistically the differential outcomes of NF-κB signaling in the heart that may be essential for future development of novel therapeutic interventions designed to target NF-κB responses and heart failure following myocardial injury.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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