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Record W2193734723 · doi:10.3390/buildings5041207

Energy Performance of Two Multi-Story Wood-Frame Passive Houses in Sweden

2015· article· en· W2193734723 on OpenAlexaboutno aff
Krushna Mahapatra, Stefan Olsson

Bibliographic record

VenueBuildings · 2015
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Passive houseElectricityArchitectural engineeringPrimary energyBuilding codeZero-energy buildingFrame (networking)EngineeringCivil engineeringEnvironmental scienceEfficient energy useGeographyTelecommunicationsArchaeologyElectrical engineering

Abstract

fetched live from OpenAlex

Two eight-story wood-framed residential buildings with the Swedish 2012 passive house standard were built in 2009 in the Portvakten Söder quarter in the city of Växjö in Sweden. In this paper, we present the monitored specific energy use of the buildings and compare to the requirements of the Swedish building code and recommendation for passive houses. We also estimated the primary energy use and CO2 emissions and investigated the tenants’ views and experiences of the two buildings. Results show that the actual specific energy use of 40.2 kWh/m2Atemp/year in the Portvakten Söder building fulfills, by a good margin, the requirements of the Swedish building code and the recommended passive house standard, but is higher than projected. Applying a marginal perspective, the calculated primary energy use and carbon dioxide emission from operating the buildings (excluding household electricity) was 40 kWh/m2Atemp/year and zero, respectively. Responses of 20 tenants to a mail-in questionnaire survey showed that over 90% were satisfied with their apartments.

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 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: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.232
Teacher spread0.211 · 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.

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

Citations13
Published2015
Admission routes1
Has abstractyes

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