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A Review of Optical Properties of Shading Devices

2008· review· en· W4231365994 on OpenAlexaff
Athanasios Tzempelikos

Bibliographic record

VenueAdvances in Building Energy Research · 2008
Typereview
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsConcordia University
Fundersnot available
KeywordsShadingMaterials scienceEngineering physicsEngineeringOpticsArchitectural engineeringEnvironmental scienceComputer sciencePhysicsComputer graphics (images)

Abstract

fetched live from OpenAlex

The optical properties of shading devices have an impact upon the daylighting and thermal performance of a building's perimeter spaces. This chapter presents an overview of past and current approaches in computing the optical properties of shading devices. Optical properties are determined by the different components of visible and solar transmittance, reflectance and absorptance. Emphasis is given to the three major types of shading used today: venetian blinds, roller shades/screens and draperies. Comparisons between experimental procedures and analytical and numerical modelling techniques are presented, and limitations in existing models and standards are discussed. The final section describes the latest generalized methods and models for characterizing complex fenestration/shading systems.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.107
GPT teacher head0.398
Teacher spread0.291 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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