Sustainable world through sustainable materials and integrated biorefineries
Bibliographic record
Abstract
The present world, with all its advancement, is not a sustainable world, simply because it is based on non-renewable raw materials (non-RRMs). Sustainable world is best expressed in terms of sustainable development and non-RRMs must be replaced by sustainable materials. The sustainable materials needed by modern society are very wide and the main pillars are biofuels and bioproducts. Both pillars are best related through integrated biorefineries (IBRs) formed of related concepts which are very important for the economic development and sustainability of all countries on our planet. Integrated biorefineries include the production of biofuels and bioproducts and utilizing novel technologies. An IBR contains at least two routes: a biochemical route based on a sugar platform and a thermochemical-catalytic route based on a syngas platform. It is a multiple inputs–multi outputs (MIMO) system with design flexibility to accept a wide range of biofeedstock, especially wastes. If the biorefinery consists of only one route/platform, or is limited with regard to MIMO or biofuels/bioproducts produced, then it should be considered an elementary biorefinery (EBR). Sustainable development engineering which is a subsystem of sustainable development (and sustainable world) is more general than Environmental Engineering; and Clean and Green Technology, because it also includes the utilization of RRMs to achieve not only sustainability but also clean environment. An integrated system approach based on system theory is used to analyse sustainable development, sustainable world, sustainable materials, IBRs, EBRs and their interactions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".