Determination of Bromine Stable Isotopes Using Continuous-Flow Isotope Ratio Mass Spectrometry
Bibliographic record
Abstract
A new methodology for bromine stable isotope determination by continuous-flow isotope ratio mass spectrometry (CF-IRMS) was developed. The technique was tested on inorganic samples. Inorganic bromide was precipitated in the form of silver bromide by using silver nitrate in a standard methodology. Bromine stable isotope analysis was carried out on methyl bromide (CH3Br) after converting silver bromide to methyl bromide by reacting it with methyl iodide (CH3I). The system used in this study is an IsoPrime IRMS, with analytical capabilities of both dual-inlet and continuous-flow modes coupled with an Agilent 6890 GC equipped with a CTC Analytics CombiPAL autosampler. This new technique measures samples as small as 0.2 mg of AgBr (1 micromol of Br-). The bromine stable isotope analysis using continuous flow technology showed excellent precision and accuracy. The internal precision using pure methyl bromide gas is better than +/-0.03 per thousand (+/-SD); the external precision using seawater standard is better than +/-0.06 per thousand (+/-SD) for n = 12. Moreover, the sample analysis time is 16 min, as compared to 75 min needed in previous techniques. This allows for 50 samples to be analyzed in 1 day, as compared to 8 samples using the conventional techniques. A series of natural saline formation waters and brines from sedimentary and crystalline rock environments was measured by this new methodology to test the potential natural range of delta81Br. The bromine isotopic composition of the samples ranged from 0.00 to +1.80 per thousand relative to standard mean ocean bromide (SMOB). Initial trends and distinctive isotopic difference were noticed between crystalline shield brines and sedimentary formation brines.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".