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Record W2913276187 · doi:10.33137/cpoj.v1i2.32026

MODULAR PRINCIPLE TO PRODUCE ACTIVE PROSTHETIC HAND

2018· article· en· W2913276187 on OpenAlexvenueaboutno aff
Anton Kruglov, Gregory Lein, И. В. Шведовченко

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicDigital Transformation in Industry
Canadian institutionsnot available
Fundersnot available
KeywordsAmputationModular designPresentation (obstetrics)Modularity (biology)OrthoticsMedicineComputer sciencePhysical medicine and rehabilitationOrthodonticsSurgeryOperating system

Abstract

fetched live from OpenAlex

INTRODUCTION We analyzed the functional prostheses including body powered prosthesis1 produced for partial hand amputation. There are almost no solutions on the world market for patients with partial hand amputation. There is no final solution for stump socket (inner socket) that could present both comfort for the stump and cosmetic look of the socket, and at the same time had partial possibility to take the load and transfer it to the power unit.2,3 Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32026/24443 How to cite: Kruglov A, Lein G, Shvedovchenko I. MODULAR PRINCIPLE TO PRODUCE ACTIVE PROSTHETIC HAND. CANADIAN PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, POSTER PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32026 Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. http://www.aopanet.org/

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.228
Teacher spread0.216 · 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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