Estimating the required logistical resources to support the development of a sustainable corn stover bioeconomy in the <scp>USA</scp>
Bibliographic record
Abstract
Abstract In this study, the logistical resources required to develop a bioeconomy based on corn stover in the USA are quantified, including field equipment, storage sites, transportation and handling equipment, workforce, corn growers, and corn lands. These resources are essential to mobilize large quantities of corn stover from corn fields to biorefineries. The logistical resources are estimated over the lifetime of the biorefineries. Seventeen corn‐growing states are considered for the logistical resource assessment. Over 6.8 billion gallons of cellulosic ethanol can be produced annually from 108 million dry tons of corn stover in these states. The maximum number of required field equipment (i.e., choppers, balers, collectors, loaders, and tractors) is estimated to be 194 110 units with a total economic value of about $26 billion. In addition, 40 780 trucks and flatbed trailers would be required to transport bales from corn fields and storage sites to biorefineries with a total economic value of $4.0 billion. About 88 899 corn growers need to be contracted with an annual net income of over $2.1 billion. About 1903 storage sites would be required to hold 53.1 million dry tons of inventory after the harvest season. These storage sites would take up about 35 320.2 acres and 4077 loaders with an economic value of $0.4 billion would handle this inventory. The total required workforce to run the logistics operations is estimated to be 50 567. The magnitude of the estimated logistical resources demonstrates the economic and social significance of the corn stover bioeconomy in rural areas in the USA. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".