The Contributions of Biomass Supply for Bioenergy in the Post-COVID-19 Recovery
Bibliographic record
Abstract
This research investigates how biomass supply chains (BSChs) for bioenergy within the broader bioeconomy could contribute to the post-COVID-19 recovery in three dimensions: boosting economic growth, creating jobs, and building more resilient and cleaner energy systems in four future scenarios, in the short term (by 2023) and long term (by 2030). A SWOT analysis on BSChs was used for generating a questionnaire for foresight by a two-round Delphi study. To interpret the results properly, a short survey and literature review is executed to record BSChs behavior during the pandemic. In total, 23 (55% response rate) and 28 (46% response rate) biomass experts from three continents participated in the Delphi and the short survey, respectively. The strongest impact from investment in BSChs would be on economic growth, followed by a contribution to the resilient and cleaner energy systems and job creation. The effects would be more visible in the long- than in the short-term period. Investments with the most impact on recovery are those that improve biomass material efficiency and circularity. Refurbishment of current policies to enhance the supply of biomass as a renewable resource to the future economy is a must.
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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 | 0.001 |
| 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".