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Record W2096005191 · doi:10.1115/esda2014-20223

Determining of Optimized Mechanical Characters for Designing of an Artificial Ankle

2014· article· en· W2096005191 on OpenAlexaff
Ali Moazemi Goudarzi, Hossein Bisheh, Mohammad Fazeli, Misagh Imani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAnkleActuatorMechanism (biology)Computer scienceSpring (device)Artificial muscleMechanical designGaitSimulationArtificial intelligenceEngineeringControl theory (sociology)Physical medicine and rehabilitationStructural engineeringMechanical engineeringControl (management)PhysicsMedicine

Abstract

fetched live from OpenAlex

Investigating the mechanical behavior of a healthy human ankle shows that it can be simulated by a mechanism composed of simple elements such as spring, and actuator. Hence, appropriate design of this mechanism can be resulted to an artificial ankle that can help amputees properly. Researches show that whatever the biomechanical behavior of artificial ankle is similar to that of natural ankle, it can be used by consuming less energy. Considering biomechanical behavior of normal ankle in a walking gait, required parameters for designing of an artificial ankle composed of springs and electromechanical actuator will be determined. Finally, to verify the suggested model, a prototype will be materialized and tested.

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 score0.438
Threshold uncertainty score0.205

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 head0.017
GPT teacher head0.240
Teacher spread0.223 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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