A Post-Mission Analysis of Housing Suppliers' Perceptions to the Solar Photovoltaic Homes
Bibliographic record
Abstract
The Earth is heating up and global warming is conspicuous today. Carbon dioxide (CO2) gas generated by the burning of fossil fuels and the forests and it is responsible for about half the greenhouse gas warming. Notably, the energy used to heat, light and run our homes accounts for 27 % of all the CO2 emissions in the UK. One of the most promising renewable energy technologies is a solar photovoltaic (PV) power generating system that can be integrated into today’s homes. This paper identifies design, production and marketing approaches being applied successfully by Japanese housing manufacturers for the commercialisation of their PV solar homes. As well, this analyses housing producers’ perception or emotional attachment to such innovative green houses by documenting their experience of participating in the Japan Solar Photovoltaic Manufactured Housing Technical Mission that was organised in 2006 by Natural Resources Canada, where the author acted as the mission coordinator. This study may provide guidelines on how to increase the number of early adopters of PV solar housing and how to commercialise such homes that conventional homebuilders and housing manufacturers are often not familiar with.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".