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Record W2921448383 · doi:10.5206/uwomj.v87i2.1161

Brain controlled robotic arms - advancements in prosthetic technology

2019· article· en· W2921448383 on OpenAlexvenueno aff
Sean Wong, Chloe Gui

Bibliographic record

VenueUniversity of Western Ontario Medical Journal · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsProsthesisArtificial limbsProsthetic handPhysical medicine and rehabilitationMedicineComputer scienceEngineeringSurgeryArtificial intelligence

Abstract

fetched live from OpenAlex

A prosthesis is a medical tool used to replace a missing body part. They are designed to restore both functionality and form to the patient user. There has been a rich history in the field or prosthetics extending back centuries. However, recent advancements have led to the development of more sophisticated and innovative prosthetic technology, such as the brain controlled myoelectric prosthetic limb. While current prosthesis options such as the passive prosthetic and body-powered prosthetic have their respective limitations, the myoelectric prosthetic limb offers an unheralded level of functionality for patients. This article will seek to discuss current and ongoing advancements in the field of prosthetics, with specific regards to artificial limbs. There will be discussion of the history of prosthesis and current prosthesis options for patients, with assessment of their respective benefits and limitations.

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)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.003

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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
GenreReview

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
Published2019
Admission routes1
Has abstractyes

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