Chemical characterization of snowfall in Shinjo, Yamagata Prefecture, Japan and long-term trend of snow acidification during 1991/92 to 2002/03
Bibliographic record
Abstract
新庄市における降雪の化学組成の特徴について明らかにすることを目的に，1999-2000年冬季（1999/00）から2002-2003年冬季（2002/03） までの4冬季間に降雪を1日毎に採取し，pH, 電気伝導度（EC）および主要化学成分の濃度について検討を行った．その結果，各冬季とも全試料中の70％以上がpH5.0以下の酸性雪であり，その平均値は4.7から4.9の範囲であった． 海塩起源成分は， 北西の風が吹いた際に高くなる傾向が認められた． 酸性化成分のnss SO4 2-は同じ酸性化成分のNO3-に比べてやや高く，nas SO4 2-/NO3-当量濃度比からNO3- は主に採取地近傍起源であり， 高濃度のnss SO4 2-濃度が認められた試料については， 大陸からの長距離輸送成分の影響を受けた可能性が示唆された．アルカリ成分であるnss Ca2+濃度は，黄砂の飛来に伴い濃度が上昇していることが確認された．また，これまでに報告されているデータも加えた1991年から2003年までの11冬季における降雪の酸性度の経年変動についても検討した結果， 年々酸性化が進展しており， その酸性化には主にNO3-が寄与している可能性が高いことが明らかとなった．
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".