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Record W4242188521 · doi:10.32920/ryerson.14655708.v1

Barn Adaptation: A Proposal To Protect Rural Architecture

2021· preprint· en· W4242188521 on OpenAlexaffabout
Ashley D. Stewart

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsArchitectureCompromiseAdaptive reuseRural areaEnvironmental planningReuseResource (disambiguation)Adaptation (eye)GeographyArchitectural engineeringRural developmentCivil engineeringBusinessEngineeringComputer sciencePolitical scienceArchaeologyAgriculture

Abstract

fetched live from OpenAlex

The countryside that surrounds the Greater Toronto Area possesses a significant amount of Canada's prime farmland. However, to accommodate urban growth, this precious resource is being converted to provide urban developments. The area of interest for this thesis is the rural-urban fringe, a zone of transition between working farms, rural communities and urban residential developments. The developments that are built in this area illustrate a common development approach, the elimination of all obstacles, including farmland and rural architecture. This thesis introduces the concept of an alternative approach for suburban development, one that presents a compromise between rural and urban needs. At the heart of this concept is the design project, the adaptive reuse of a barn that serves as a tool to communicate the unique qualities of these monumental buildings. It also identifies the need to rethink suburban development approaches to include the preservation of rural architecture and prime farmland.

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)0.004
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.012
Scholarly communication0.0060.003
Open science0.0020.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.032
GPT teacher head0.230
Teacher spread0.198 · 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
GenreOther

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
Published2021
Admission routes2
Has abstractyes

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