Assessment of Moisture Effect in Simulating Forestry Biomass Supply Chain Strategy: Case Study of New Brunswick, Canada
Bibliographic record
Abstract
In order to investigate the effect of variation of the moisture content of forest biomass residues on a supply chain strategy, a simulation was performed using integrated biomass supply analysis and logistics modeling. A simple supply chain strategy was chosen and applied for Miramichi and Plaster Rock, two different regions in New Brunswick, Canada. These regions are selected based on three criteria: annual potential harvest of forest biomass residues, annual production potential of electric and thermal energy and distribution of transportation zones. The moisture content of forest biomass residues was dependant on the weather conditions of the selected regions. The results show that the moisture content of the biomass in Plaster Rock was more stable but higher than the biomass in the Miramichi region. In simulating the supply chain strategy, particular attention is given to harvest, baling, storage and transportation of the biomass. The simulation results show that, during harvest and baling of the biomass, the moisture content affects the dry matter loss and, as a consequence, the customer and ownership costs of the operations. It also affects the energy input and the quantity of carbon dioxide released in the atmosphere. However, dry matter loss and accordingly the cost of the operations are the main parameters affecting the storage and transportation of forest biomass residues.
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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) | 0.000 | 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 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".