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Record W4234754775 · doi:10.32920/ryerson.14656560

Architecture as palimpsest : a strategy of intermediacy

2021· preprint· en· W4234754775 on OpenAlexaffabout
Ke Leng Tran

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsArchitectureSchema (genetic algorithms)Architectural engineeringPalimpsestContext (archaeology)AestheticsHistorySociologyComputer scienceEngineeringArtArchaeology

Abstract

fetched live from OpenAlex

In much of historic preservation work, artefacts are primarily seen as documents of their time and bearing little relevance to how we design buildings and cities today. Consequently, architectural interventions separate the old and new work, unintentionally distancing historic buildings from their evolving context. There are layers of inspiration embedded within an existing site that can enrich architectural creations. The history of architecture is the story of built forms that have been altered and re-created to make space for the continuation of life. This thesis seeks an archtictural strategy that not only complements but also challenges and reveals the history and material character of the original intent, in order to create greater meaning for the historic building. As a hypothesis, the thesis project presents a schema for the conversion of century old public school in the City of Toronto into a contemporary art museum that demonstrates this strategy, arguing that engaging with the existing work can lead to new insights and meanings.

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)0.009
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0100.042
Scholarly communication0.0200.024
Open science0.0030.028
Research integrity0.0030.006
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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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 designTheoretical or conceptual
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

Citations5
Published2021
Admission routes2
Has abstractyes

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