Development of <i>in situ</i> Li isotope analysis using laser ablation quadrupole inductively coupled plasma mass spectrometry
Bibliographic record
Abstract
Rationale Lithium isotope geochemistry is an important tool in the studies of Earth and planetary materials. In situ Li isotope analyses are typically performed using secondary ion mass spectrometry (SIMS) or laser ablation multicollector inductively coupled plasma mass spectrometry (LA‐MC‐ICPMS), but these instruments are not widely accessible. Here, the capability of laser ablation quadrupole ICPMS for conducting Li isotopic analyses is evaluated. Methods An array of MPI‐DING and USGS silicate glass reference materials was analyzed repeatedly over the course of 6 months. These materials range from komatiite to rhyolite in terms of silica content (45.5–75.6 wt%) with 9–45 ppm Li. Their Li isotope compositions have been previously characterized so that matrix effects could be tested with these reference materials. Analyses were conducted using an NWR193 laser ablation system coupled to an Agilent 7900 ICPMS system. Results Analytical precision is primarily limited by Li concentration in the samples. For samples with ~9 ppm Li, the internal precision is 6‰ (2 SD, 150 μm spot diameter), whereas that for a sample with ~45 ppm Li is 4‰ (2 SD, 120 μm spot diameter). The technique is somewhat sensitive to sample matrix: samples with SiO 2 content that deviates from the bracketing standard display fractionated δ 7 Li, necessitating correction using a session‐specific matrix correction curve. Conclusion Lithium isotope analysis by ns‐LA‐QICPMS is worthwhile for samples with high Li concentrations and when a matrix‐matched standard can be obtained. Although the precision of this method is not as high as those achievable with SIMS and LA‐MC‐ICPMS, it remains adequate for resolving large isotope fractionations found in natural and laboratory settings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.017 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".