The Use of Polyvinylchloride (PVC) Claddings and Polystyrene Wall Panels as Alternative Building Materials to Wood: A Strategy to Combat Climate Change.
Bibliographic record
Abstract
Unprecedented variations in climate are currently being experienced all over the world and Nigeria is not an exemption from this global trend. Generally, researchers have pointed to human activities as the major contributor. The paper evaluates occupants’ perception and acceptability of Polyvinylchloride (PVC) claddings and Polystyrene wall units as substitutes for wood based products at Royal Estate in Lagos.This paper also examines alternative building materials as a remedy to deforestation in building construction activities in Nigeria with a view to highlighting their mutilating effect on climate change. A total of 20 dwelling units were studied; using Post Occupancy Evaluation (POE) research method. Results show that 90% of respondents rated as ‘good’ their level of acceptability and awareness of these materials while quality and durability were rated equally as ‘good’ by 75% of total respondents.From the general high level of acceptability of Polyvinylchloride (PVC) claddings and Polystyrene wall units, if popularized could serve as alternative building materials. This may reduce the dependence on wood which could therefore, mitigate against the negative impact of climate change.Government has been advised to make and implement reforestation policies so that trees could serve as carbon sink.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".