Carbon Dioxide Equivalent Emissions of Newly Developed Rice Varieties
Bibliographic record
Abstract
Breeding of rice varieties with low carbon dioxide equivalent (CO2e) emission is essential in reducing global greenhouse gas (GHG) emissions. In this study, we compared the gross CO2e emission of two newly developed green super rice (GSR) varieties with elite hybrids and nationally released farmer-cultivated varieties from production to post-production in the dry and wet seasons in Laguna, Philippines. The average gross CO2e emission was 17.9 tons CO2e ha-1 or 2.98 tons CO2e ton-1 rice (production 82%, post-production 18%). Contributing to this total were soil emissions at 72%, the use of chemicals at 5%, burning of rice straw at 3%, cooking at 12%, and transportation at 5%. The average social cost of carbon (SCC) per ton of rice was estimated at $119. Increasing grain yield per unit area with shorter growth duration decreased CO2e emission of rice per unit of weight. Cultivation of rice varieties GSR8 and GSR2 emitted 37.0% lower CO2e than the popular inbred varieties.
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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 | 0.000 |
| 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 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".