Greenhouse gas emissions from cranberry fields under irrigation and drainage in Quebec
Bibliographic record
Abstract
Agricultural management practices influence the fluxes of greenhouse gases by altering the physical, biological and chemical environment of the soil. Cranberry farming is of particular concern because production takes place on soils with high water tables and the fields are flooded at various times of the year. These conditions initiate reductive processes which lead to the production of greenhouse gases. Weekly dark chamber flux measurements of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) were taken in two farmed cranberry fields in Quebec over the 2012 and 2013 growing seasons. Findings show that commercial cranberry fields are not significant sources of greenhouse gases throughout most of the growing season. CO2, CH4 and N2O fluxes ranged from 1-142 CO2-C m-2 hr-1, -0.01 to 0.04 mg CH4-C m-2 hr-1, and -0.0013 to 0.0013 mg N2O-N m-2 hr-1, respectively. However, when the fields are flooded during the spring melt and for harvest, they become sources of carbon dioxide and methane. Fields that remain flooded for extended periods of time thus emit significantly more greenhouse gases than those which are flooded and drained quickly.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".