Continuous Measurements of Belowground Nitrous Oxide Concentrations
Bibliographic record
Abstract
Nitrous oxide released from soil is a concern since it can act as a potential atmospheric pollutant and it represents a loss of N from the soil. To better understand the factors controlling N 2 O production and transport, we developed a system to obtain continuous measurements from below the soil surface. The sampling system pulls small volumes of soil gas from buried sample probes through a tunable diode laser trace gas analyzer. The advantage of this system is that it measures concentrations spectroscopically, allowing regular, continuous measurements. This provides it with the distinct advantage of being able to capture short‐term changes in gas concentrations that may be important for nutrient and greenhouse gas budgeting. Furthermore, the system is relatively simple to install and could be integrated into existing field measurements of trace gas flux. Measurements of belowground N 2 O concentrations were obtained during the spring thaw from buried probes in a conventionally tilled field that was planted in soybean [ Glycine max (L.) Merr.] the previous summer. Measurements showed that belowground N 2 O concentrations at the 25‐cm depth varied between 65 and 85 μmol mol −1 before snowmelt. After melting of the snow and the beginning of the soil thawing, N 2 O concentrations decreased to a value generally <1 μmol mol −1 During this period when belowground N 2 O concentrations were near atmospheric values, wind speed influenced concentrations, possibly through a pressure pumping effect.
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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 | 0.000 | 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 | 0.001 |
| 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 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".