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Record W2590654791 · doi:10.1016/j.ifacol.2016.12.157

Investigating ‘Exo-Skeleton’ Design and Fabrication Challenges for the Hand Region Using Material Extrusion Processes

2016· article· en· W2590654791 on OpenAlexaff
Hamed Kalami, André Salim Khayat, Jill Urbanic

Bibliographic record

VenueIFAC-PapersOnLine · 2016
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBraceExtrusionParametric designFabrication3D printingManufacturing engineeringComputer scienceParametric statisticsEngineeringMechanical engineeringMaterials scienceMedicineMathematics

Abstract

fetched live from OpenAlex

Orthotic brace design and manufacturing can be problematic for people who have physical dimensions in the 5th or 95th percentile regions, or for people with unique chronic conditions. Advanced manufacturing tools provide opportunities to realize specialty braces. The goal in this research paper is to investigate solutions for finger and hand brace design and fabrication. Parametric design approaches are taken, and select solutions are presented, which have been fabricated using material extrusion processes. Research in this area is ongoing as many practical issues have been raised throughout this project.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.252
Teacher spread0.196 · 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 teacher head, 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

Citations2
Published2016
Admission routes1
Has abstractyes

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