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Record W3181973031 · doi:10.1016/j.rser.2021.111359

Test rooms to study human comfort in buildings: A review of controlled experiments and facilities

2021· review· en· W3181973031 on OpenAlexaff
Anna Laura Pisello, Ilaria Pigliautile, Maedot S. Andargie, Christiane Berger, Philomena M. Bluyssen, Salvatore Carlucci, Giorgia Chinazzo, Zs. Deme Belafi, Bing Dong, Matteo Favero, Ali Ghahramani, George Havenith, Arsalan Heydarian, D. Kastner, Minjin Kong, Dusan Licina, Yapan Liu, Alessandra Luna-Navarro, Ardeshir Mahdavi, Alessandro Nocente, Marcel Schweiker, Marianne F. Touchie, Marika Vellei, Filippo Vittori, Andreas Wagner, Aijia Wang, Shen Wei

Bibliographic record

VenueRenewable and Sustainable Energy Reviews · 2021
Typereview
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversity of Toronto
FundersInnovációs és Technológiai MinisztériumNemzeti Kutatási Fejlesztési és Innovációs HivatalEuropean CommissionNorges ForskningsrådAgence Nationale de la RechercheVillum FondenSyracuse UniversityNational Research, Development and Innovation OfficeNemzeti Kutatási, Fejlesztési és Innovaciós AlapNational Science Foundation
KeywordsThermal comfortArchitectural engineeringTest (biology)EngineeringEnvironmental scienceAeronauticsMeteorologyGeography

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0040.004
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.297
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations71
Published2021
Admission routes1
Has abstractno

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