Recycling and reuse of solid wastes; a hub for ecofriendly, ecoefficient and sustainable soil, concrete, wastewater and pavement reengineering
Bibliographic record
Abstract
Abstract Ecofriendly, ecoefficient and sustainable civil engineering work has been research with emphasis on adapting the byproducts of solid waste recycling and reuse to achieving infrastructural activities with low or zero carbon emission. The direction combustion model, the solid waste incinerator caustic soda oxides of carbon entrapment model (SWI-NaOH-OCEM) developed by this research has achieved a zero carbon release. This research adopted the literature search method to put together research results of previous works relevant to the aim of this present work. It has been shown that CO and CO2 emissions can be contained during the derivation of alternative or supplementary cementing materials used in the replacement of ordinary Portland cement in civil engineering works. In the overall assessment of the present review work has left the environment free of the hazards of CO and CO2 emissions. It was shown that these supplementary cementing materials derived from solid wastes improve the engineering properties of treated soft clay and expansive soils, concrete, and asphalt. Bio-peels, another form solid waste has been established as a good detoxificant used in treating wastewater. It has been shown that solid waste recycling and reuse is a hub to achieving ecofriendly, ecoefficient and sustainable infrastructural development on the global 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".