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Record W4243539053 · doi:10.1201/b18046-18

Preparing regulatory challenges and opportunities for small to medium residential scale stabilized rammed earth buildings in Canada

2015· book-chapter· en· W4243539053 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMedieval Architecture and Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsRammed earthScale (ratio)Architectural engineeringEarth (classical element)Civil engineeringEnvironmental scienceEngineeringGeotechnical engineeringGeographyCartographyPhysics

Abstract

fetched live from OpenAlex

Before the adoption of the objective-based model code, non-conforming materials and designs were permitted on a project by project basis, either via the building official’s discretion, via some type of approved research program, or because of exceptional circumstances. An example of the 1 INTRODUCTION Authorities having jurisdiction in Canada are currently in their second code cycle since the introduction of an objective-based national model code. The first National Building Code of Canada (NBCC) to adopt an objective-based format was issued in 2005. The Canadian Commission on Building and Fire Codes attempts to re-issue an updated version of the major codes (Building, Fire, Plumbing & Electrical) every 5 years. The current national model building code is the 2010 edition, with a 2015 edition on pace to be issued late in 2015 or early 2016. (Canadian Commission on Building and Fire Codes, in press) The move to an objective-based code did not eliminate the listing of prescriptive solutions for a given building assembly, rather it involved adding alternative regulatory paths to acceptable solutions. By defining the goals of the code via building official’s discretion is given in the first case study below. An approved research program is most often a case where a municipality and an academic institution cooperate to demonstrate a novel building technique that is funded publicly. Exceptional circumstances are really an extreme case of this; for instance, an Olympic village or World’s Fair site. It is not the purpose of this paper to deal with projects of that magnitude per se, rather the example is given because those projects are also designed, permitted, insured and funded-simply at a scale much higher than small to medium scale residential builds.

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)0.008
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 score0.162
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0170.005
Scholarly communication0.0110.002
Open science0.0040.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.108
GPT teacher head0.234
Teacher spread0.126 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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