Bibliographic record
Abstract
【はじめに】今回，Vancouver分類に基づいて当院における大腿骨ステム周囲骨折の治療成績を検討した．【対象】2018年1月～2023年6月に当院で大腿骨ステム周囲骨折の治療を行った9例で，受傷時のVancouver分類はtype B1：3例，type B2：6例，全例セメントレスステムTHAであった．治療はtype B1の3例に骨接合術を行い，type B2の2例に骨接合術，4例にステム再置換術を行った．検討項目として臨床評価は手術内容，免荷期間，先行手術から骨折までの期間，歩行能力，合併症とし，画像評価はステム沈下量，骨癒合の有無とした．【結果】全例で骨癒合が得られたが，type B1の1例に歩行能力の低下を認めた．合併症はtype B2で浅層感染1例，大転子骨折1例を認めた．type B2の骨接合を行った2例にステム沈下を認めた．【まとめ】当院での大腿骨ステム周囲骨折の治療成績は概ね良好であった．Vancouver分類type B2での骨接合術の適応は先行手術から骨折までの時期により考慮し得ると思われた．
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".