MPI‐DING reference glasses for in situ microanalysis: New reference values for element concentrations and isotope ratios
Bibliographic record
Abstract
We present new analytical data of major and trace elements for the geological MPI‐DING glasses KL2‐G, ML3B‐G, StHs6/80‐G, GOR128‐G, GOR132‐G, BM90/21‐G, T1‐G, and ATHO‐G. Different analytical methods were used to obtain a large spectrum of major and trace element data, in particular, EPMA, SIMS, LA‐ICPMS, and isotope dilution by TIMS and ICPMS. Altogether, more than 60 qualified geochemical laboratories worldwide contributed to the analyses, allowing us to present new reference and information values and their uncertainties (at 95% confidence level) for up to 74 elements. We complied with the recommendations for the certification of geological reference materials by the International Association of Geoanalysts (IAG). The reference values were derived from the results of 16 independent techniques, including definitive (isotope dilution) and comparative bulk (e.g., INAA, ICPMS, SSMS) and microanalytical (e.g., LA‐ICPMS, SIMS, EPMA) methods. Agreement between two or more independent methods and the use of definitive methods provided traceability to the fullest extent possible. We also present new and recently published data for the isotopic compositions of H, B, Li, O, Ca, Sr, Nd, Hf, and Pb. The results were mainly obtained by high‐precision bulk techniques, such as TIMS and MC‐ICPMS. In addition, LA‐ICPMS and SIMS isotope data of B, Li, and Pb are presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".