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Record W4288329236 · doi:10.48550/arxiv.1906.05710

RodSteward: A Design-to-Assembly System for Fabrication using 3D-Printed\n Joints and Precision-Cut Rods

2019· preprint· W4288329236 on OpenAlexaff
Alec Jacobson

Bibliographic record

VenuearXiv (Cornell University) · 2019
Typepreprint
Language
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRodFabricationInterface (matter)Computer scienceContext (archaeology)Engineering drawing3d printedFocus (optics)VisualizationJoint (building)Mechanical engineeringEngineeringStructural engineeringManufacturing engineeringArtificial intelligenceOpticsParallel computing

Abstract

fetched live from OpenAlex

We present RodSteward, a design-to-assembly system for creating\nfurniture-scale structures composed of 3D printed joints and precision-cut\nrods. The RodSteward systems consists of: RSDesigner, a fabrication-aware\ndesign interface that visualizes accurate geometries during edits and\nidentifies infeasible designs; physical fabrication of parts via novel fully\nautomatic construction of solid 3D-printable joint geometries and automatically\ngenerated cutting plans for rods; and RSAssembler, a guided-assembly interface\nthat prompts the user to place parts in order while showing a focus+context\nvisualization of the assembly in progress. We demonstrate the effectiveness of\nour tools with a number of example constructions of varying complexity, style\nand parameter choices.\n

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.007

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 head0.086
GPT teacher head0.210
Teacher spread0.123 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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Same venuearXiv (Cornell University)Same topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207