Comprehensive <scp>P</scp>b‐<scp>S</scp>r‐<scp>N</scp>d‐<scp>H</scp>f isotopic, trace element, and mineralogical characterization of mafic to ultramafic rock reference materials
Bibliographic record
Abstract
Abstract Controlling the accuracy and precision of geochemical analyses requires the use of characterized reference materials with matrices similar to those of the unknown samples being analyzed. We report a comprehensive Pb‐Sr‐Nd‐Hf isotopic and trace element concentration data set, combined with quantitative phase analysis by XRD Rietveld refinement, for a wide range of mafic to ultramafic rock reference materials analyzed at the Pacific Centre for Isotopic and Geochemical Research, University of British Columbia. The samples include a pyroxenite (NIM‐P), five basalts (BHVO‐2, BIR‐1a, JB‐3, BE‐N, GSR‐3), a diabase (W‐2), a dolerite (DNC‐1), a norite (NIM‐N), and an anorthosite (AN‐G); results from a leucogabbro (Stillwater) are also reported. Individual isotopic ratios determined by MC‐ICP‐MS and TIMS, and multielement analyses by HR‐ICP‐MS are reported with 4–12 complete analytical duplicates for each sample. The basaltic reference materials have coherent Sr and Nd isotopic ratios with external precision below 50 ppm (2SD) and below 100 ppm for Hf isotopes (except BIR‐1a). For Pb isotopic reproducibility, several of the basalts (JB‐3, BHVO‐2) require acid leaching prior to dissolution. The plutonic reference materials also have coherent Sr and Nd isotopic ratios (<50 ppm), however, obtaining good reproducibility for Pb and Hf isotopic ratios is more challenging for NIM‐P, NIM‐N, and AN‐G due to a variety of factors, including postcrystallization Pb mobility and the presence of accessory zircon. Collectively, these results form a comprehensive new database that can be used by the geochemical community for evaluating the radiogenic isotope and trace element compositions of volcanic and plutonic mafic‐ultramafic rocks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".