Possibility of utilizing agriculture biomass as a renewable and sustainable future energy source
Bibliographic record
Abstract
Issues related to depletion of conventional fuel resources and environmental concerns have become the driving force to explore an environment friendly, renewable, economical and sustainable alternate energy source. Huge quantities of agriculture biomass are being produced globally which can be transformed to biofuels by utilizing various procedures. However, issues such as environmental damages and competing uses of agriculture biomass need to be investigated factually considering the short as well as long-term acuity considering its effect on the soil and conversion to biofuels. This review provides an insight into the potential of various biomass as an energy source. Presently available conversion techniques to convert biomass to energy in various phases are discussed. The review also addresses the technical, socio-economic and environmental concerns and limitations with the appropriate control measures. Present study revealed that by the year 2020 most of the developed countries including the USA, Canada, China and Poland are switching to, renewable energy including agriculture biomass. Techno-economic analysis performed shows the feasibility of utilizing agriculture biomass as a competitive energy source. The information provided will help stakeholders, energy managers and decision makers working in the sustainable and renewable energy sectors to consider agriculture biomass for energy production at a larger scale.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".