A Mathematical Model to Predict CO2 Emission from Woody Biomass Storage Piles
Bibliographic record
Abstract
Biomass is promising to substitute petroleum-based products in generating bioenergy due to its potential to release less greenhouse gas (GHG) during processing. However, this opinion has been challenged. Two biomass piles established for bioenergy purpose were studied. Moisture contents for pile 1 and 2 were 51.1% before storage, then increased to 57.6% for pile 1 after 192-day storage; and 56.9% for pile 2 after 114 days. Overall pile densities of pile 1 and 2 were 169.4 and 165.3 kg-od/m3, respectively, with compaction taken into account (9.2% for pile 1 and 10.1% for pile 2). Total dry matter losses were 16.2% and 14.9% for pile 1 and 2, respectively. Consequently, pile 1 released 0.194 grams CO2 per gram dried biomass during storage; while pile 2 produced 0.178 grams CO2 per gram dried biomass. The CO2 emission during storage was found to be much higher than that generated from harvest and transport.
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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) | 0.003 | 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".