Probing the <scp><sup>186</sup>Os</scp>/<scp><sup>188</sup>Os</scp> Precision Barrier: New Recommended Values for the <scp>DROsS</scp> Reference Material and an Assessment of Mixed 10<sup>11</sup> and 10<sup>12</sup> Ω Amplifier Arrays
Bibliographic record
Abstract
We present high precision negative ion thermal ionisation mass spectrometry (N‐TIMS) Os isotope measurement results for the DROsS isotope reference material (iCRM), to investigate the limits on the precision of TIMS‐based 186Os/188Os results. We used analytical conditions previously highlighted to optimise precision, present a new flexible data processing protocol, and measured 184Os intensities on a Faraday Cup equipped with an amplifier using a 1012 Ω resistor. Despite a measurement procedure that minimised uncertainty contributions from counting statistics and Johnson‐Nyquist noise, the intermediate measurement precision of our approach does not significantly improve on previous high precision Os isotope measurements, with the exception of 184Os/188Os. This is probably due to uncertainties in measured amplifier gain factors, which are greater when using mixed arrays of 1011 and 1012 Ω resistors than when using 1011 Ω resistors alone, though Faraday Cup deterioration could also contribute. We propose that multi‐dynamic Os isotope measurements could largely eliminate both of these uncertainties. Our 184Os/188Os measurement results are the most precise yet, yielding 184Os/188Os = 0.0013036 ± 0.0000007 (2s, n = 38). Additionally, we average our data with published data to recommend the following isotope ratios for DROsS: 186Os/188Os = 0.1199319 ± 0.0000024, 187Os/188Os = 0.1609227 ± 0.0000022, 189Os/188Os = 1.219709 ± 0.000010, 190Os/188Os = 1.983793 ± 0.000011.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".