Y-ravnotežni test zgornjega dela
Bibliographic record
Abstract
IzvlečekNamen izdelave diplomske naloge je bil zbrati in predstaviti vse normativne vrednosti za Y-ravnotežni test zgornjega dela.Znanstveno literaturo smo iskali v bazah PubMed in Scopus, en članek pa smo vključili po nesistematičnem iskanju v bazi GoogleScholar.Izmed 66 člankov, ki smo jih uvrstili v ožji izbor, smo jih 14 izločili zaradi nedostopnosti oziroma pomanjkljivega poročanja.Pregled literature je razkril veliko heterogenost preiskovancev, zato smo rezultate v preglednicah predstavili po športih oziroma smo jih v preglednice umestili po smislu.Zbrane normativne vrednosti smo predstavili po spolu, starosti, športu in drugih preiskovanih ključih.Po pregledu literature ugotavljamo, da se je Y-ravnotežni test zgornjega dela izkazal za zanesljiv.V večini raziskav ni mogoče zaznati statistično značilnih razlik med stranema ali med spoloma, vseeno pa opažamo, da moški v primerjavi z ženskami dosegajo boljše rezultate.Sistematično predstavljeni rezultati bodo služili kot dober vodnik normativnih vrednosti za trenerje in druge posameznike, ki nameravajo test uporabiti.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".