Re‐evaluation of the hydrogen stable isotopic composition of keratin calibration standards for wildlife and forensic science applications
Why this work is in the frame
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Bibliographic record
Abstract
Rationale Determination of non‐exchangeable hydrogen isotopic compositions ( δ 2 H values) of bulk complex organic materials is difficult due to uncontrolled H isotope exchange between the organic material and ambient water vapor. A number of calibration keratinous materials with carefully measured hydrogen isotopic compositions of the non‐exchangeable fraction were proposed to enable stable isotope laboratories to normalize their 2 H measurements. However, it was recently reported that high‐temperature carbon‐reactor methods for measuring the hydrogen isotopic composition of nitrogenous organic materials is biased by the production of HCN in the reactor. As a result, the reported values of these calibration materials needed to be re‐evaluated. Methods We evaluated the non‐exchangeable δ 2 H VSMOW values of keratins EC1 (CBS) and EC2 (KHS), USGS hair standards, and a range of other nitrogenous widely used organic laboratory calibration materials (collagen and chitin) using pre‐treatment with a preparation device designed to eliminate residual moisture and quantify exchangeable H. Results The revised non‐exchangeable δ 2 H VSMOW values of EC‐1 (CBS) and EC‐2 (KHS) keratin standard materials were –157.0 ± 0.9 and –35.3 ± 1.1 ‰, respectively. The revised values of USGS42 and USGS43 were –72.2 ± 0.9 and –44.2 ± 1.0 ‰, respectively, in excellent agreement with previous results. Conclusions For routine H isotope analyses, with proper sample pre‐treatment, we show that the Comparative Equilibration approach can provide accurate and reproducible non‐exchangeable δ 2 H values among laboratories regardless of the reactor type used. © 2017 Her Majesty the Queen in Right of Canada Rapid Communications in Mass Spectrometry © 2017 John Wiley & Sons Ltd. Reproduced with the permission of the Environment and Climate Change Canada.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it