Bibliographic record
Abstract
Adipose tissue has emerged as a major endocrine organ producing a wide spectrum of hormones and factors that play crucial roles in regulating cell turnover and function, not only locally within the adipose tissue but also in the brain and other key metabolic organ systems. It is known that gene activity is controlled at both transcriptional and post-transcriptional levels. Consequently, one of the most important means by which the activity of a gene is assessed is through the determination of levels of the corresponding messenger ribonucleic acid (mRNA). This process involves the isolation of total cellular RNA and subsequent analysis of the mRNA of interest. Given the unique nature of adipose tissue and adipocytes (i.e., containing high amounts of lipid), special RNA isolation techniques that have been tested in both white adipose tissue and isolated mature adipocytes from rats and mice will be presented. Although several methods are available for mRNA quantitation, we will describe a real-time quantitative reverse transcription polymerase chain reaction protocol because of its superior sensitivity and reliability.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.017 | 0.016 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".