Pyrolysis-GC/MS analysis of leachates for differentiating the parent matter of DOM
Bibliographic record
Abstract
The purpose of this study was to better understand the link between dissolved organic matter (DOM) in soil leachates and the different vegetation cover types in a boreal forest. Soil cores were collected from the Caribou Poker Creeks Research Watershed (CPCRW) and subjected to a laboratory leaching procedure. The leachates were subjected to a number of analytical tests, including pyrolysis-gas chromotagraphy/mass spectrometry (py-GC/MS). Py-GC/MS is a molecular fingerprinting technique that proved capable of characterizing the DOM obtained from the various soil leachates. The molecular fingerprint and vegetation types were compared with Student's t test and principal component analysis. Results from these tests support a conclusion that the characteristics of cover vegetation can be detected in leachates. Coniferous and deciduous trees could be statistically differentiated based on their molecular fingerprints with statistical significance (p < 0.005). By using, the combination of py-GC/MS and rigorous multivariate statistical analysis one can better understand the source of DOM based on characteristics it retains. Key words: py-GC/MS, DOM, molecular fingerprint, leachate.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".