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Record W2062232724 · doi:10.1016/j.egypro.2014.11.1011

Design of Net Zero Energy Buildings: Feedback from International Projects

2014· article· en· W2062232724 on OpenAlexaff
François Garde, Aurélie Lenoir, Alessandra Scognamiglio, Daniel Aelenei, D. Waldren, Harald Nils Røstvik, Josef Ayoub, Laura Aelenei, Michael Donn, Monique Tardif, Shaan Cory

Bibliographic record

VenueEnergy Procedia · 2014
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsGovernment of CanadaNatural Resources Canada
Fundersnot available
KeywordsZero-energy buildingBenchmarkingArchitectural engineeringWork (physics)Net (polyhedron)Agency (philosophy)Zero (linguistics)Energy (signal processing)Task (project management)Energy conservationBaseline (sea)EngineeringComputer scienceCivil engineeringBusinessSystems engineeringMathematicsPolitical scienceMechanical engineeringElectrical engineeringSociology

Abstract

fetched live from OpenAlex

The International Energy Agency (IEA), through the Solar Heating and Cooling programme (SHC) Task 40 and the Energy Conservation in Buildings and Community Systems programme (ECBCS, now named EBC) Annex 52, works towards developing a common understanding and setting up the basis for an international definition framework for Net Zero Energy Buildings (Net ZEBs). One of the subtasks of this programme–SubTaskC focuses benchmarking the Net ZEBs around the world to identify the innovative solutions sets that makes up this new type of building. This paper presents an overview of the work conducted by the participants of Subtask C and of Zero Energy Building projects that have been identified.

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)0.016
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.008
GPT teacher head0.178
Teacher spread0.170 · 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 designObservational
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

Citations36
Published2014
Admission routes1
Has abstractyes

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