Bibliographic record
Abstract
Dear friends, The European Union has changed its approach toward scientific publications and we have to respect the new guidelines. The most important guideline is that all scientific articles have to be openly accessible. While our journal already has open access to articles, we will try to number articles by digital object identifier (DOI) by the end of the year. It will be slightly more work, but generally we will still be able to publish three issues per year. At the end of May new journal evaluations have been published in SCOPUS. Unfortunately, our citation has been placed slightly lower than last year, but our SNIP indicator has risen and thus our journal is now in the second quarter of journals. An excellent result! In this issue, we have again ten articles by authors from Brazil, Portugal, Canada, Greece, Denmark (for the first time), Bulgaria (for the first time), Great Britain, Japan, Croatia, Germany, the USA, the Czech Republic and Slovakia. There is a variety of research fields and it is good to see that there is a lot of productive international cooperation among researchers. Among articles on gymnastics disciplines, most are dealing with the man and the women artistic gymnastics; we are proud that for the first time we have an article from TEAMGYM, a discipline that is gaining momentum in Europe. Anton Gajdoš prepared another article related to the history of gymnastics, refreshing our information on Albert Azarjan, an excellent Armenian (ex Soviet Union) gymnast. Please be welcome to Freiburg to 13th International Gymnastics Congress. Just to remind you, if you quote the Journal, its abbreviation on the Web of Knowledge is SCI GYMN J. I wish you pleasant reading and a lot of inspiration for new research projects and articles, Ivan Čuk Editor-in-Chief
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 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.160 | 0.102 |
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".