Measurement of <sup>13</sup>C and <sup>15</sup>N Isotopic Composition on Nanomolar Quantities of C and N
Bibliographic record
Abstract
We describe a trapping and chromatography system that cryogenically removes CO(2) and N(2) generated from sample combustion in an elemental analyzer (EA) and introduces these gases into a low-flow helium carrier stream for isotopic analysis. The sample size required for measurement by this system (termed nano-EA/IRMS) is almost 3 orders of magnitude less than conventional EA analyses and fills an important niche in the range of analytical isotopic methods. Only 25 nmol of N and 41 nmol of C are needed to achieve 1.0 per thousand precision (2sigma) from a single measurement while larger samples and replicate measurements provide better precision. Analyses of standards demonstrate that nano-EA measurements are both accurate and precise, even on nanomolar quantities of C and N. Conventional and nano-EA measurements on international and laboratory standards are indistinguishable within analytical precision. Likewise, nano-EA values for international standards do not differ statistically from their consensus values. Both observations indicate the nano-EA measurements are comparable to conventional EA analyses and accurately reproduce the VPDB and AIR isotopic scales. Critical to the success of the nano-EA system is the procedure for removing the blank contribution to the measured values. Statistical treatment of uncertainties for this procedure yields an accurate method for calculating internal and external precision.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".