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
Macrophages play essential roles in tissue homeostasis, pathogen elimination, and tissue repair. A defining characteristic of these cells is their ability to efficiently adapt to a variety of abruptly changing and complex environments. This ability is intrinsically linked to a capacity to quickly alter their transcriptome, and this is tightly associated with the epigenomic organization of these cells and, in particular, their enhancer repertoire. Indeed, enhancers are genomic sites that serve as platforms for the integration of signaling pathways with the mechanisms that regulate mRNA transcription. Notably, transcription is pervasive at active enhancers and enhancer RNAs (eRNAs) are tightly coupled to regulated transcription of protein-coding genes. Furthermore, given that each cell type possesses a defining enhancer repertoire, studies on enhancers provide a powerful method to study how specialization of functions among the diverse macrophage subtypes may arise. Here, we review recent studies providing insights into the distinct mechanisms that contribute to the establishment of enhancers and their role in the regulation of transcription in macrophages.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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