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Record W4319319647 · doi:10.3390/en16041587

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

2023· article· en· W4319319647 on OpenAlexaff
Christiane Berger, Ardeshir Mahdavi, Eleni Ampatzi, Sarah Crosby, Runa T. Hellwig, Dolaana Khovalyg, Anna Laura Pisello, Astrid Roetzel, Adam Rysanek, Marika Vellei

Bibliographic record

VenueEnergies · 2023
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversity of British Columbia
FundersAustrian Science Fund
KeywordsScope (computer science)Thermal comfortContext (archaeology)Quality (philosophy)Architectural engineeringScientific evidenceComputer scienceManagement scienceRisk analysis (engineering)EngineeringBusinessMathematics

Abstract

fetched live from OpenAlex

Professionals in the building design and operation fields typically look at standards and guidelines as a reliable source of information and guidance with regard to procedural, contractual, and legal scope and requirements that are relevant to accountability issues and compliance necessities. Specifically, indoor environmental quality (IEQ) standards support professionals to bring about comfortable thermal, air quality, acoustic, or visual conditions in buildings. In this context, it appears essential to regularly examine the IEQ standards’ applicability and scientific validity. The present contribution focuses on common thermal comfort standards in view of the reasoning and includes evidence behind their recommendations and requirements. Thereby, several international and national thermal comfort standards are examined via a structured matrix to assess basic parameters, design and performance variables targeted by the standards, suggested value ranges, and both general and specific evidence from the scientific literature. Finally, this paper discusses findings and points to the identified gaps in the chain of evidence from the results of scientific studies and the recommendations included in the thermal standards. As such, the present contribution has the potential to inform future developments regarding transparent and evidence-based thermal standards.

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 score0.137
Threshold uncertainty score0.286

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 head0.019
GPT teacher head0.224
Teacher spread0.205 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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