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Record W2620727905 · doi:10.1080/13556207.2017.1330385

Sustainable conservation strategies for Canada’s modernist wood legacy

2017· article· en· W2620727905 on OpenAlexaffabout
Susan M. Ross

Bibliographic record

VenueJournal of Architectural Conservation · 2017
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsCarleton University
Fundersnot available
KeywordsSustainabilityArchitectureContext (archaeology)EngineeringArchitectural engineeringSustainable developmentCivil engineeringLandscape architectureNature ConservationEnvironmental resource managementEnvironmental planningGeographyEnvironmental sciencePolitical scienceArchaeologyEcology

Abstract

fetched live from OpenAlex

The object of this paper is to advance concrete strategies for integrating objectives of environmental sustainability in the conservation of wood elements in Canadian modernist architecture. To do so, the paper considers: how wood and engineered wood products were used in modern building in Canada; how environmental values associated with wood in modern architecture have evolved; and what new issues are raised by current sustainable forestry and building practices. Finally, preliminary strategies are suggested for integrated approaches to conserving modern wood, which will be of value beyond the Canadian context.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.558

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.003
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.023
GPT teacher head0.234
Teacher spread0.211 · 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
Published2017
Admission routes2
Has abstractyes

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