Three certified sugar reference materials for carbon isotope delta measurements
Bibliographic record
Abstract
Rationale For isotope delta analysis, it is preferable to have at least two matrix‐matched reference materials whose isotope delta values encompass those of the samples to be analyzed. The National Research Council Canada (NRC) has developed three sugar Certified Reference Materials (CRMs), BEET‐1 (beet sugar), GALT‐1 (galactose), and FRUT‐1 (fructose), to be collectively used for carbon isotope delta measurements in sugars, and other organic materials. Methods All materials were homogenized and packaged in glass ampules. All three sugar materials were analyzed at the NRC using elemental analyzer/isotope ratio mass spectrometry (EA/IRMS). Six additional laboratories also provided EA/IRMS measurements. Data from all laboratories were re‐normalized using three international secondary reference materials (IAEA‐CH‐6, USGS40, and USGS62) included as blind samples in the inter‐laboratory comparison, thus providing added quality control and robustness to the study. Results Re‐normalized carbon isotope delta values from each laboratory were combined using a random laboratory effects statistical model with accounting of the correlations between the laboratory results due to the use of the same reference materials for calibration. The consensus δ( 13 C) values and combined standard uncertainties which include effects due to characterization, homogeneity, and stability for BEET‐1, GALT‐1, and FRUT‐1 are −26.02(7) ‰, −21.41(6) ‰, and −10.98(5) ‰, respectively, on the VPDB scale. Conclusions Three new δ( 13 C) sugar CRMs (BEET‐1, GALT‐1, and FRUT‐1) were developed and are available from NRC. These three CRMs can be utilized as a set for daily δ( 13 C) scale normalization of sugar‐based or other organic materials in order to produce reliable δ( 13 C) measurements.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".