Bibliographic record
Abstract
The last two decades have seen one of the greatest excitements and discoveries in science, gasotransmitters in biology and medicine. Leading the trend by nitric oxide and extending the trudge by carbon monoxide, here comes hydrogen sulfide (H(2)S) who builds up the momentum as the third gasotransmitter. Being produced by different cells and tissues in our body, H(2)S, alone or together with the other two gasotransmitters, regulates an array of physiological processes and plays important roles in the pathogenesis of various diseases from neurodegenerative diseases to diabetes or heart failure, to name a few. As a journal dedicated to serve the emergent and challenging field of H(2)S biology and medicine, Antioxidant and Redox Signaling assembles the most recent discoveries and most provoking ideas from leading scientists in H(2)S fields, which were communicated in the First International Conference of H(2)S in Biology and Medicine, and brings them to our readers in two Forum Issues. Through intellectual exchange and intelligent challenge with an open-mind approach, we can reasonably expect that sooner rather than later the exploration of metabolism and function of H(2)S will provide solutions for many of the biological mysteries of life and pave way for the arrival of many more gasotransmitters.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".