Improved Advanced Biomass Logistics Utilizing Woody and other Feedstocks in the Northeast and Pacific Northwest (Final Report)
Bibliographic record
Abstract
Willow and poplar short rotation woody crops (SRWC) have shown promise with regards to environmental benefits and rural development but wide adoption lags due to underdeveloped markets and supply systems. High costs associated with harvesting, handling and transportation (40-60% of delivered cost) have impeded expansion. A better understanding of these systems will create opportunities to improve efficiency, reduce costs, and realize environmental benefits and impacts. The project’s goal was to lower the delivered cost of hybrid poplar in the Northwest and willow in the Northeast by optimizing harvesting and logistics supply systems while maintaining or improving biomass quality along the supply chain. Over 3,400 Mg of biomass and 300 ha of willow and poplar were monitored over a range of crop and field conditions. Feedstock quality as affected by storage and preprocessing were shown to improve or maintain feedstock quality. Modeled harvesting costs ranged from $38–61 Mg-1 dry; when including delivery and preprocessing feedstock costs ranged between $79-83 Mg-1 dry for willow and $106-116 Mg-1 dry for poplar. Costs for willow minimized when hot water extraction and high-moisture densification preprocessing were used. Models also suggest that social and regional factors could further reduce costs. Results will give guidance to feedstock growers, harvesting and logistic operations, biorefinery project developers, and policy makers developing SRWC to support a growing bioeconomy.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".