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Record W2008111124 · doi:10.1260/1478077054214460

3-Axis CNC Milling in Architectural Design

2005· article· en· W2008111124 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Architectural Computing · 2005
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsProcess (computing)Scale (ratio)Rapid prototypingEngineeringEngineering drawingFocus (optics)Manufacturing engineeringPresentation (obstetrics)Computer scienceMechanical engineeringSystems engineeringProgramming language

Abstract

fetched live from OpenAlex

Physical scale models still have a role in architectural design. 3-axis CNC milling provides one way of making scale models both for study purposes and for presentation in durable materials such as wood. We present some types of scale models, the methods for creating them and the place in the design process that scale models occupy. We provide an overview of CNC milling procedures and issues and we describe the process of how one can creatively develop appropriate methods for milling different types of scale models and materials. Two case studies are presented with which we hope to convey not only the range of possible models that can be machined but also the way one creatively explores to arrive at appropriate milling strategies. Where apposite, we compare 3-axis CNC milling to newer technologies used for rapid prototyping but rapid prototyping is not a primary focus.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.240
Teacher spread0.229 · 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