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Record W2781949041

BUILDING ENVELOPE OPTIMAZATION METHOD AND APPLICATION TO THREE HOUSE TYPES IN A PROPOSED SOLAR DISTRICT ENERGY SYSTEM

2012· article· en· W2781949041 on OpenAlexaboutno aff
Chris Kirney, Anil Parekh, Keith Paget

Bibliographic record

VenueProceedings of SimBuild · 2012
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsActivity-based costingSingle-family detached homeEfficient energy useSolar energyInvestment (military)Scale (ratio)Energy (signal processing)Cost effectivenessArchitectural engineeringEngineeringEnvironmental scienceComputer scienceOperations managementElectrical engineeringBusinessMathematicsGeography
DOInot available

Abstract

fetched live from OpenAlex

A simple cost optimization method was applied to determine the appropriate investment in energy efficiency for houses to be built as part of a large scale solar community planned for construction near Calgary, Alberta. The cost effectiveness of individual house envelope energy efficiency upgrades was determined using energy simulation results and builder contributed costing information. These results then guided the combination of house energy efficiency upgrades. Finally, the incremental costs of these combined upgrades were compared to the estimated incremental cost of providing space heating using the planned solar district heating system to determine the appropriate house energy efficiency upgrades.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2012
Admission routes1
Has abstractyes

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