Bibliographic record
Abstract
2000年から2011年に大腿骨ステム周囲骨折に対して当院にて手術を行った8症例について検討した．男性2例，女性6例で，手術時年齢は66～90歳（平均81歳）であった．初回手術は人工骨頭置換術が6例，人工股関節置換術が2例であった．骨折型はVancouver分類でB1が5例，Cが3例で，経過観察期間は2～16カ月（平均5.3カ月）であった．8例中4カ月以上フォローできた6例では良好な仮骨形成を認め，最終経過観察時の歩行能力は8例中7例が自力歩行可能であった．大腿骨ステム周囲骨折は，治療に難渋することが多く，通常の骨接合より高度な技術が必要とされる．近年高齢化社会に大腿骨ステム周囲骨折も増加しており，今後予防法や治療法の確立が求められる．
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.094 | 0.031 |
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".