Determination of Cd in Seawater at ng L<sup>&minus;1</sup> Levels by ICP-MS: Removal of Mo during Chelating-resin Solid-phase Extraction
Bibliographic record
Abstract
誘導結合プラズマ質量分析法（ICP-MS）で海水中ng L－1レベルのCdを定量する際に問題となるMoOの干渉を低減するために，キレート樹脂濃縮分離法におけるMoの選択的除去法を確立した．イミノ二酢酸を官能基に有するキレート樹脂固相カラムを使用し，海水試料に容積比で過酸化水素を2％ 添加することで，濃縮液中のMo濃度を0.1 μg L－1以下に低減することができた．その結果，ICP-MSによるCdの分析においてMoOによる多原子イオン干渉を完全に除去することが可能となった．本法を用いてpH 5.0において海水試料の25倍濃縮を実施した場合の添加回収率は98.6±1.0％（n＝4），分析検出限界は0.06 ng L－1であり，非汚染海域のCdの分析に十分適用可能なレベルであった．また，Fe, Ni, Cu, Zn, Pb, 希土類元素等の同時濃縮も可能であることが分かった．本法の有効性は，National Research Council Canada（NRCC）より頒布されている海水認証標準物質の分析により確認した．また，実際試料としてサンゴ礁海域の海水試料の分析に適用し，数ng L－1レベルのCdを精度よく定量することができた．
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 teacher head, 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".