Data for growing season nitrous oxide emissions from a Gray Luvisol as a function of long-term fertilization history and crop rotation
Bibliographic record
Abstract
A field study conducted over five growing seasons (2013-2017) assessed the effect of long-term fertilization history and crop rotation on growing season nitrous oxide (N2O) and carbon dioxide (CO2) emissions, wheat yield, wheat N uptake, N2O emission intensity and soil properties on Gray Luvisolic soils. Long-term fertility treatments included check, manure, NPKS, NPK and PKS fertilizers in two contrasting crop rotations: a 2-year of wheat (Triticum aestivum L.)-fallow (WF), and a 5-year wheat (Triticum aestivum L.)-oat (Avena sativa)-barely (Hordeum vulgare L.) - alfalfa (Medicago sativa)/brome (Bromus tectorum) hay (WOBHH). Rotation significantly affected cumulative growing season N2O emissions and, within each rotation, long-term fertilizer or manure N additions increased N2O emissions over the check. Average, cumulative growing season N2O emissions from the 5-year rotation were 1.29 kg N2O-N ha-1, significantly higher than the 0.58 kg N2O-N ha-1 in the WF rotation, but N2O emission intensities were comparable between to the two rotations. Cumulative N2O emissions were positively correlated to total soil N (0-15 cm) and wheat N uptake, but N2O emission intensities were negatively correlated to total soil N.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".