Delivered cost of switchgrass pellets transported from depots to a biorefinery in the Piedmont, <scp>USA</scp>
Bibliographic record
Abstract
Abstract The southeast region of the USA has the potential to be a significant producer of biobased products; however, research is needed to demonstrate the most cost‐effective feedstock delivery system. This study considers a distributed network of five pellet depots to supply feedstock (i.e., switchgrass pellets) for the operation of a hypothetical biorefinery located near South Boston, VA, USA. The study was divided into four main categories: (1) feedstock delivery from satellite storage locations (SSLs) to the pellet depots; (2) pellet production at the depots; (3) pellet storage at the depots, and (4) pellet delivery to the biorefinery to supply a continuous operation 24 h per day, 7 days per week, and 48 weeks per year. The cost analysis begins with round bales in SSLs and ends when a load of pellets arrives at the biorefinery. This study does not include a farmgate payment to grow, harvest, and store round bales in SSLs, and it also does not include receiving facility operations at the biorefinery. The weighted average cost for annual delivery to the biorefinery from the five depots was USD 129.32 per Mg pellets. The division of this cost was 51% feedstock delivery, 38% pelleting, 2% pellet storage, and 9% pellet delivery. The cost for the smallest depot was USD 145.37 per Mg pellets, in comparison with USD 115.22 per Mg pellets for the largest depot. These results indicate an economy‐of‐scale influence; there was a 21% reduction in cost as the depot size increased from 66 450 to 140 430 Mg pellets per year.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".