A dual-isotope approach to allow conclusive partitioning between three sources
Bibliographic record
Abstract
Stable isotopes have proved to be a transformative tool; their application to distinguish between two sources in a mixture has been a cornerstone of biogeochemical research. However, quantitatively partitioning systems using two stable isotopes (for example, (13)C and (12)C) has been largely limited to only two sources, and systems of interest often have more than two components, with interactive effects. Here we introduce a dual-isotope approach to allow conclusive partitioning between three sources, using only two stable isotopes. We demonstrate this approach by partitioning soil CO2 emissions derived from microbial mineralization of soil organic carbon (SOC), added pyrogenic organic matter (PyOM) and root respiration. We find that SOC mineralization in the presence of roots is 23% higher (P<0.05) when PyOM is also present. Being able to discern three sources with two isotopes will be of great value not only in biogeochemical research, but may also expand hitherto untapped methodologies in diverse fields.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".