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
Epidemiological studies and clinical trials revealed that chronic consumption coffee is associated with the inhibition of several metabolic diseases as well as reduction in overall and cause-specific mortality. We show that both natural and decaffeinated brands of coffee similarly rapidly trigger autophagy in mice. One to 4 h after coffee consumption, we observed an increase in autophagic flux in all investigated organs (liver, muscle, heart) in vivo, as indicated by the increased lipidation of LC3B and the reduction of the abundance of the autophagic substrate sequestosome 1 (p62/SQSTM1). These changes were accompanied by the inhibition of the enzymatic activity of mammalian target of rapamycin complex 1 (mTORC1), leading to the reduced phosphorylation of p70(S6K), as well as by the global deacetylation of cellular proteins detectable by immunoblot. Immunohistochemical analyses of transgenic mice expressing a GFP-LC3B fusion protein confirmed the coffee-induced relocation of LC3B to autophagosomes, as well as general protein deacetylation. Altogether, these results indicate that coffee triggers 2 phenomena that are also induced by nutrient depletion, namely a reduction of protein acetylation coupled to an increase in autophagy. We speculate that polyphenols contained in coffee promote health by stimulating autophagy.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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