Bibliographic record
Abstract
砂地ほ場で、ゲルフ式ウェルパーミアメータ(GP)法の適用性を調べた。当試験法は、 1985年前後にカナダのGuelph大学の研究グループによって開発されたもので、オーガーで掘削した半径教 cm 程度のウェル内に一定水位を保ち、そのときに生じる定常浸潤量を測定して、ほ場における飽和透水係数 K_ を測定するものである。一連の試験より、測定装置のシンプルさ、測定の簡便さと迅速性といった原位置試験法としての優れた性能を確認できた。測定精度も、十分に実務的なものであった。深さ140cm まで実施した GP法からえられたK_ と、その後に掘削したトレンチでの土層断面の観察結果および採取コア土の透水係数との対比を行った。GP法は、試験条件と土質に応じた測定領域をもつため、層構造をもつほ場では、この測定額域に含まれる土層を平滑したようなK_ を算出すること、また砂地ほ場のように相対的に透水性の高い土壌では、主に鉛直方向の透水係数を測定することが分かった。
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".