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Record W3120423758 · doi:10.1108/ohi-03-2012-b0002

Design Principals of Narrow Townhouse; For Affordability and Adaptability

2012· article· en· W3120423758 on OpenAlexaff
Avi Friedman, Robyn Whitwham

Bibliographic record

VenueOpen House International · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsMcGill University
Fundersnot available
KeywordsCeiling (cloud)AdaptabilityArchitectural engineeringWindow (computing)FootprintKey (lock)EngineeringComputer scienceCivil engineeringGeographyStructural engineeringComputer security

Abstract

fetched live from OpenAlex

Recognized for their high density and resources conservation, townhouses are attracting homebuyers and builders once again. With housing affordability being an issue in many nations, the interior and the exterior must be cost effective. Their proportions, however, pose a particular design challenge. The typically narrow width limit design options and the long footprint restrict the amount of light that reaches the dwelling's center. This article presents strategies used by designers of notable townhouses with a width smaller than 6 meters to best solve those challenges. The authors studied interior design of 28 narrow units and drew conclusions about key principles that facilitated their planning. The research demonstrates that space efficiency can be achieved by employing open plans, minimizing circulation, using light colors, varying ceiling heights, suitable window placement and creative storage fixtures.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.003

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 head0.131
GPT teacher head0.309
Teacher spread0.178 · 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
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
Published2012
Admission routes1
Has abstractyes

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