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Record W7004618413

Shirley Wang

2020· article· en· W7004618413 on OpenAlexaboutno aff

Bibliographic record

VenueSOURCE Sheridan's Institutional Repository (Sheridan College) · 2020
Typearticle
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsnot available
Fundersnot available
KeywordsBuilding envelopeCladding (metalworking)Building constructionBuilding scienceBambooFacadeBuilding materialEfficient energy useEnvelope (radar)
DOInot available

Abstract

fetched live from OpenAlex

The exterior building envelope is designed with sustainable and durable materials with light-weight steel construction method that hopes to create a modern, and energy efficient building design. Exterior cladding uses natural wood siding that enhances the modern and natural exterior aesthetics of the building while maintaining low carbon-foot print by using locally sourced and rapidly reproducible wood material. The natural and light-toned materials continues to the interior space with bamboo flooring and timber wood-work that brings the natural exterior environment to the interior space. High thermal resistant insulation materials (expanded polystyrene, fiber board sheathing, and fiberglass) along with air-tight envelope design increases the building energy efficiency by reducing heating and cooling loss. Light-weight steel construction using steel beams, girders, columns and open web steel joists on top of a concrete foundation system creates a durable and reliable building structure that is easy to build with low construction costs. The simple, rectangular massing with straight edges further simplifies the construction process and creates a minimalist, modern design that is consistent with current architectural projects. The proposed architectural and structural design for the renovation of Brampton Fire-station 204 seeks to modernize the existing building while ensuring sustainability, reduced carbon footprint, and simplicity in construction.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.188
Teacher spread0.179 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueSOURCE Sheridan's Institutional Repository (Sheridan College)Same topicFire dynamics and safety researchFrench-language works237,207