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
Mammalian hibernators offer natural models for investigating solutions to the metabolic injuries that accrue during cold ischemic storage of human organs removed for transplant. Knowledge of the biochemical mechanisms that regulate and stabilize metabolism to ensure long-term viability in the hypometabolic, hypothermic state of hibernation could lead to applied treatments that could increase the time that excised organs can be maintained in cold storage and/or improve recovery of function after implantation. New research has documented the widespread role of reversible protein phosphorylation control of metabolism in achieving the coordinated suppression of metabolic rate that greatly extends viability during torpor. Analysis of hibernation-induced gene expression is proving to be of crucial importance for identifying the genes and proteins that are up-regulated to address organ-specific concerns during torpor. In particular, the power of complementary deoxyribonucleic acid (cDNA) array screening is identifying families of proteins that are up-regulated during hibernation (eg, serpins, heat shock proteins, antioxidants, membrane transporters) and highlighting previously unrecognized areas of cellular metabolism as contributing to the hibernation phenotype. These offer new targets for innovative applied treatments that could enhance cyto-protection and cold ischemia survival of organ explants.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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