KOŠTANO-HRSKAVIČNI PRIJELOM IVERA KAO POSLJEDICA AKUTNE LUKSACIJE
Bibliographic record
Abstract
Deskriptori: I{~a{enje patele -komplikacije; Zglobna hrskavica -ozljede; Hrskavi~ni prijelomi -etiologija, dijagnoza, kirurgija; Ko{tani prijelomi -etiologija, dijagnoza, kirurgija; Zglobni ligamenti -kirurgija; Patelofemoralni zglob -kirurgija Sa`etak.Akutna luksacija ivera ozljeda je mladih sporta{a i posljedica je nepovoljnih biomehani~kih odnosa, kao i anatomskih odstupanja u podru~ju koljenskog zgloba.U tim nepovoljnim okolnostima naglim i sna`nim napinjanjem ~etveroglavog mi{i}a natkoljenice mo`e do}i do lateralne luksacije ivera.Prikazali smo slu~aj mladog mu{karca s akutnom luksacijom ivera te posljedi~nim ko{tano-hrskavi~nim prijelomom.Iako je rendgenska slika pokazala uredan nalaz koljena, tipi~na anamneza, klini~ki pregled i MR koljena pretrage su kojima se postavlja dijagnoza, a onda je dijagnoza ozljede indikacija za operacijsko ili konzervativno lije~enje.Artroskopski je potvr|ena dijagnoza, prona|en je ko{tano-hrskavi~ni ulomak i u~vr{}en vijcima te tako u~injena rekonstrukcija zglobne povr{ine ivera.Poja~ani su medijalni, a opu{teni lateralni stabilizatori ivera i uspostavljen je njegov anatomski klizni put.Drugim kirur{kim zahvatom u~injen je »second look« te su izva|eni vijci.Pravodobnim operativnim lije~enjem, rekonstrukcijom zglobne plohe i provedenom rehabilitacijom postigli smo dobar anatomski i funkcionalni rezultat.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.013 |
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".