A–Z of nutritional supplements: dietary supplements, sports nutrition foods and ergogenic aids for health and performance—part 12
Bibliographic record
Abstract
As usual, the alphabet throws together a mixture of supplements with different levels of popularity and scientific support. Part 20 covers some rarely reported, studied and/or little used supplements in sport: glycine, histidine and inosine. The majority of human studies of supplementation with the essential amino acid histidine has involved clinical work. In terms of athletic performance, there is current interest in supplementation strategies to increase muscle content of the histidine-containing dipeptide (HCD), carnosine. Despite some interest in the use of a chickenbreast extract (CBEX) described in this article, most of the focus in this area involves â-alanine supplementation (covered in part 5). There was some interest in inosine as an ergogenic aid in the 1990s but it appears not to have been studied since then. Meanwhile, there appears little role for glycine supplementation in sport although some interest in glycine-containing compounds is possible. β-Hydroxymethyl β-butyrate (HMB) is much more well known, with marketing usually targeting bodybuilders.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.018 |
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".