Bibliographic record
Abstract
残腎機能（RRF）は，透析患者にとって生命予後およびQOL維持に関連する重要な指標といわれる。尿量はRRFの1 つの測定指標であるが，それ以外にRRFの測定指標として，溶質排泄能あるいは有機酸排泄能なども指標の1 つといわれている。しかし，RRFの定義および測定指標は完全には確立してないにもかかわらず，尿量あるいは溶質クリアランスが増加すると生命予後とQOLが改善する事実は指摘されている。また，肥満，高血圧，糖尿病などの生活習慣病はRRFを減少させることも指摘されている。逆にRRFが減少すると高血圧などは悪化することも指摘されており，これらの生活習慣病とRRFとの間に双方向性の関連がある。具体的なRRFの維持方法としては，incremental hemodialysisなどの透析方法の工夫，あるいは利尿薬や降圧薬の使用が有効といわれている。
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".