MC‐ICP‐MS Isotope Measurements with Direct Injection Nebulisation (d‐DIHEN): Optimisation and Application to Boron in Seawater and Carbonate Samples
Bibliographic record
Abstract
We report here an optimisation of the demountable direct injection high efficiency nebuliser (d‐DIHEN) for isotopic measurements with a Neptune (ThermoFisher Scientific, Bremen, Germany) multi‐collector inductively coupled plasma‐mass spectrometer (MC‐ICP‐MS) and describe a method for boron isotopic ratio determination. With direct injection nebulisation 100% of the analyte was introduced into the ICP‐MS plasma and wash times were drastically reduced for elements such as boron and thorium. Compared to the classical stable introduction system (SIS: double Scott/cyclonic spray chamber), sensitivity for boron was 2–5 times higher with d‐DIHEN and wash times up to ten times shorter. Repeatability of 11B/10B sample‐calibrator bracketing measurements reached 0.25‰ (2s) for seawater and coral samples. Method accuracy and reproducibility were tested on mixed reference solutions having δ11B values in the ranges −90 to +40‰ and −2 to +2.5‰, demonstrating our ability to distinguish δ11B values with differences of only 0.25‰. The international seawater reference material NRCC NASS‐5 (National Research Council, Ottawa, Canada), analysed in different sessions over a 10‐month period, yielded an average δ11B value of +39.89 ± 0.25‰, in the upper range of previously published seawater values. A comparison between δ11B determined by d‐DIHEN MC‐ICP‐MS and positive‐TIMS (P‐TIMS) for four modern corals showed an excellent agreement (with bias of less than 0.4‰).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".