Nickel Isotope Variations in Terrestrial Silicate Rocks and Geological Reference Materials Measured by <scp>MC</scp>‐<scp>ICP</scp>‐<scp>MS</scp>
Bibliographic record
Abstract
Although initial studies have demonstrated the applicability of N i isotopes for cosmochemistry and as a potential biosignature, the N i isotope composition of terrestrial igneous and sedimentary rocks, and ore deposits remains poorly known. Our contribution is fourfold: (a) to detail an analytical procedure for N i isotope determination, (b) to determine the N i isotope composition of various geological reference materials, (c) to assess the isotope composition of the B ulk S ilicate E arth relative to the N i isotope reference material NIST SRM 986 and (d) to report the range of mass‐dependent N i isotope fractionations in magmatic rocks and ore deposits. After purification through a two‐stage chromatography procedure, N i isotope ratios were measured by MC ‐ ICP ‐ MS and were corrected for instrumental mass bias using a double‐spike correction method. Measurement precision (two standard error of the mean) was between 0.02 and 0.04‰, and intermediate measurement precision for NIST SRM 986 was 0.05‰ (2 s ). Igneous‐ and mantle‐derived rocks displayed a restricted range of δ 60/58 N i values between −0.13 and +0.16‰, suggesting an average BSE composition of +0.05‰. Manganese nodules (Nod A1; P1), shale ( SDO ‐1), coal ( CLB ‐1) and a metal‐contaminated soil ( NIST SRM 2711) showed positive values ranging between +0.14 and +1.06‰, whereas komatiite‐hosted N i‐rich sulfides varied from −0.10 to −1.03‰.
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 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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".