Development Perspectives Of The Biobased Economy: A Review
Bibliographic record
Abstract
ABSTRACT This paper provides an outline of the biobased economy, its perspectives for agriculture and, more particularly, for development purposes. Possibilities of development of biobased products, advanced biofuels, and viable and efficient biorefinery concepts are explored. The paper lists non‐fuel bioproducts (e.g., chemicals, pharmaceuticals, biopolymers) and presents basic principles and development options for biorefineries that can be used to generate them alongside biofuels, power, and by‐products. One of the main challenges is to capture more value from existing crops without compromising the needs and possibilities of small‐scale, less endowed farmers. Biobased products offer the most development perspectives, combining large market volumes with medium to high price levels. Consequently, the most can be expected from products like fine chemicals, lubricants, and solvents. In addition, biosolar cells can help to relax pressures on biomass production systems while decentralized production chains can serve local needs for energy, materials, and nutrients as their requirement for viable economic development are linked to larger markets. Research challenges include development of such production and market chains, and of biosolar cells and selection of model crops that offer perspectives for less favored producers and underdeveloped rural areas.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".