High‐Precision Measurement of <sup>187</sup>Os/<sup>188</sup>Os Isotope Ratios of Nanogram to Picogram Amounts of Os in Geological Samples by N‐<scp>TIMS</scp> using Faraday Cups Equipped with 10<sup>13</sup> Ω Amplifiers
Bibliographic record
Abstract
N(187Os)/N(188Os) ratios of six geological reference materials were measured using static Faraday cups (FCs) with 1013 Ω amplifiers by N‐TIMS. Our results show that the repeatability precision was 2–3‰ (2 RSD, n = 3), when taking ~ 1 g of BHVO‐2 with 76 pg g−1 of Os mass fraction and ~ 2 g of BCR‐2 with 21 pg g−1 of Os mass fraction for each sample, whether measured by FCs or by secondary electron multiplier. The repeatability precision measured by FCs was 1–0.2‰ (2 RSD, n = 3) when taking ~ 1 g of BIR‐2 with 350 pg g−1 of Os mass fraction, ~ 1 g of WGB‐1 with 493 pg g−1 of Os mass fraction or ~ 0.5 g of WPR‐1 with 13.3 ng g−1 of Os mass fraction for each sample, which is much better than those measured by secondary electron multiplier. Instead, when taking ~ 2 g of AGV‐2 with 4 pg g−1 Os mass fraction, the repeatability precision measured by secondary electron multiplier is 3–4‰ (RSD, n = 3), which is better than those measured by FCs. Of the six reference materials analysed, WPR‐1 and BIR‐1a are the most homogeneous with regard to Os isotopic composition (2 RSD of 0.08% and 0.23%, respectively) when test portion masses are 0.5–1 g.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".