Determination of Pt, Pd, Ru and Ir in geological samples by ID-ICP-MS using sodium peroxide fusion and Te co-precipitation
Bibliographic record
Abstract
A method is proposed for the determination of Pt, Pd, Ru and Ir in geological samples by isotope dilution-inductively coupled plasma mass spectrometry (ICP-MS). Mono-isotopic elements Rh and Au are determined by external calibration using Lu as the internal standard. Sodium peroxide fusion in corundum crucibles (instead of glassy carbon or zirconium crucibles) is used to decompose the samples. After dissolution of the fused cake in water, the solution is spiked with enriched stable isotopes of Pt, Pd, Ru and Ir, and then acidified with HCl. This solution is then evaporated to dryness promoting the formation of anhydrous silicate from colloidal material. PGEs and Au are then pre-concentrated by Te co-precipitation. The reagents HCl and SnCl2 are purified by Te co-precipitation. PGE blank levels are thus only derived from the Na2O2 which has PGE concentrations of <0.02 ng/g. Lutetium is added as the internal standard to correct for instrument drift and matrix suppression effects for the determination of the monoisotopic elements. Method detection limits range from 0.02 to 0.3 ng/g. The results obtained for the CCRMP (CANMET, Ottawa, Canada) certified reference materials WGB-I (gabbro), TDB-1 (diabase), UMT-1 (ultramafic ore tailings), WPR-I (altered peridotite), WMG-I (mineralized gabbro), and WMS-1 (massive sulphide) are in good agreement with certified values.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".