A critical review of the transformation of biomass into commodity chemicals: Prominence of pretreatments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biomass production has been increasing steeply with rise in population across the globe. Majority of the produced biomass has been un-utilized and thrown to landfill or discarded without proper disposal. Due to production of greenhouse gasses, possible land, and groundwater contamination due to presence of trace organic contaminants (TrOCs), various countries across the globe have implemented stringent regulations or even banned landfill for waste deposition. On the other hand, depletion in available resources and ever-increasing product demand, utilization of waste to recover value added products has been need of the hour across the globe. Biomass, a low-cost and abundant nutrient resource having a tremendous potential for replacement for fossil fuels dependence. Pre-treatments like physical, chemical, and biological were applied on biomass for product specific application recovery. However, commercialization of recovered value-added products by utilizing biomass is still far from being achieved because of social unacceptability (i.e., public acceptance) due to the presence of contaminants. So, this review discusses about utilization of various pre-treatments for recovery of commodity chemicals from biomass and it addresses how the presence of TrOCs in biomass influences the recovery of products during their conversion.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it