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Record W414985214

A Post-Mission Analysis of Housing Suppliers' Perceptions to the Solar Photovoltaic Homes

2007· article· en· W414985214 on OpenAlexaboutno aff
Masa Noguchi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSustainable Industrial Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemRenewable energyGreenhouse gasFossil fuelBusinessGlobal warmingSolar energyEnvironmental economicsArchitectural engineeringEngineeringNatural resource economicsClimate changeWaste managementEconomics
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.246
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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