Chemical Sample Processing for Combined Selenium Isotope and Selenium‐Tellurium Elemental Investigation of the Earth's Igneous Reservoirs
Bibliographic record
Abstract
Abstract The redox‐sensitive, chalcophile, and volatile Se stable isotope system offers new perspectives to investigate the origin and evolution of terrestrial volatiles and the roles of magmatic and recycling processes in the development of the redox contrast between Earth's reservoirs. Selenium isotope systematics become more robust in a well‐constrained petrogenetic context as can be inferred from Se‐Te elemental signatures of sulfides and igneous rocks. In this study, we present a high‐yield chemical sample processing method that allows the determination of Se‐Te concentrations and Se isotope composition from the same sample digest of silicate rocks by hydride generation isotope dilution (ID) quadrupole inductively coupled plasma mass spectrometry (ICP‐MS) and double spike (DS) multicollector (MC)‐ICP‐MS, respectively. Our procedure yields ∼80% Se‐Te recoveries with quantitative separation of relevant interfering elements such as Ge and HG‐buffering metals. Replicate analyses of selected international reference materials yield uncertainties better than 0.11‰ (2 s.d.) on δ 82/76 Se and 3% (r.s.d.) on Se concentration for DS MC‐ICP‐MS determinations for as low as ∼10 ng sample Se. The precision of Se‐Te concentration measurements by ID ICP‐MS is better than 3% and 5% (r.s.d.) for total amounts of ∼0.5–1 ng Se and ∼0.2–0.5 ng Te, respectively. The basaltic reference materials have variable Se‐Te contents, but their δ 82/76 Se values are rather uniform (on average 0.23 ± 0.14‰; 2 s.d.) and different from the chondritic value. This altogether provides the methodology and potential to extend the limited data set of coupled Se isotope and Se‐Te elemental systematics of samples relevant to study the terrestrial igneous inventory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".