Bibliographic record
Abstract
1999年に世界アンチ・ドーピング機構 (WADA) が設立され, 五輪では2004年アテネ開催からこのWADA規程によって行われるようになった. 毎年改訂される WADA 規程の禁止表国際基準で, 現役アスリートには使用できない薬物が示されているが, アレルギー疾患の有病率が約50%の現在, トップアスリートの治療にかかわる機会は極めて低いものの, ドーピングコントロール下にある国体選手など, 一般のアマチュア選手を治療する機会は, どの医師でもその可能性はある. 誤った知識で, アスリートに対するアレルギー性鼻炎の治療が制限され, 競技パフォーマンスを下げることがないように, どのような薬剤が禁止薬物で, どのような医療行為が禁止なのか, 医療関係者は, ある程度知識を持つ必要はある. 特に, アレルギー性鼻炎患者は, 気管支喘息やアトピー性皮膚炎の合併も少なくなく, フェキソフェナジン・プソイソエフェドリン配合薬や糖質コルチコイド, 交感神経 β 2 受容体作動薬などの正しい知識が求められる.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".