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Record W1561502092 · doi:10.3846/13928619.2007.9637803

RELEVANT CODES AND REGULATIONS: EFFECTS ON THE DESIGN OF INDUSTRIAL CONSTRUCTION

2007· article· en· W1561502092 on OpenAlexaff
Ahmed Abdallah

Bibliographic record

VenueTechnological and Economic Development of Economy · 2007
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsFunction (biology)Field (mathematics)Industrial designWork (physics)Construction engineeringComputer scienceRisk analysis (engineering)EngineeringBusinessMechanical engineering

Abstract

fetched live from OpenAlex

This paper presents the possible effects and restrictions that may arise in the field of industrial construction due to compliance with relevant construction codes and regulations, as well as the ways they can be favourably handled in the design of industrial buildings. Designs should be based primarily on human design factors, while considering the human as the centre of the work environment. Design parameters should be described as a function of both the physical and psychosocial attributes of a person as well as the technical and economical aspects in the design of industrial construction. This paper is an examination of the connection that exists between design law (codes and regulations) and industrial construction. The relevant construction laws and regulations are described, including standards and codes of practice that designing and supervising engineers are obliged to observe. Possible solutions and consequences of development in the production, constructional, and ergonomic field of design are also discussed.

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)0.023
metaresearch head score (Gemma)0.083
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.083
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0040.010
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.133
GPT teacher head0.373
Teacher spread0.240 · 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 designObservational
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

Citations1
Published2007
Admission routes1
Has abstractyes

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