A test of comparative equilibration for determining non‐exchangeable stable hydrogen isotope values in complex organic materials
Bibliographic record
Abstract
Comparative equilibration has been proposed as a methodological approach for determining the hydrogen isotopic composition (deltaD) of non-exchangeable hydrogen in complex organic materials, from feathers to blood and soils. This method depends on using homogenized standards that have been previously calibrated for their deltaD values of non-exchangeable H, that are compositionally similar to unknown samples, and that span an appropriate isotopic range. Currently no certified organic reference materials with exchangeable H exist, and so isotope laboratories have been required to develop provisional internal calibration standards, such as the keratin standards currently used in animal migration studies. Unfortunately, the isotope ratios of some samples fall outside the range of keratin standards currently used for comparative equilibration. Here we tested a set of five homogenized keratin powders as well as feathers from Painted Buntings and Dark-eyed Juncos to determine the effects of extrapolating comparative equilibration normalization equations outside the isotopic range of keratin standards. We found that (1) comparative equilibration gave precise results within the range of the calibration standards; (2) linear extrapolation of normalization equations produced accurate deltaD results to approximately 40 per thousand outside the range of the keratins standards used (-187 to -108); and (3) for both homogenized keratin powders and heterogeneous unknown samples there was no difference in variance between samples within and outside the range of keratin standards. This suggested that comparative equilibration is a robust and practical method for determining the deltaD of complex organic matrices, although caution is required for samples that fall far outside the calibration range.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".