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Record W3209374801 · doi:10.7759/cureus.19099

Design and Development of a Rotating Chair to Measure the Cervico-Ocular Reflex

2021· article· en· W3209374801 on OpenAlexaff
Praveen Sanmugananthan, Nguyen Thanh Hoai Nam, Bernadette Murphy, Ali Hosseini

Bibliographic record

VenueCureus · 2021
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsReflexGazeMedicineRotation (mathematics)Physical medicine and rehabilitationEye movementNeck painVestibulo–ocular reflexSimulationComputer visionComputer scienceOphthalmology

Abstract

fetched live from OpenAlex

Eye reflexes that stabilize gaze are essential in navigating daily life. One such reflex is the cervico-ocular reflex (COR). An important neural structure involved in the COR is the cerebellum, which facilitates proper gaze stability through sensorimotor integration to adjust eye movements accordingly. This reflex is tested by fixating the head in space and rotating the body around the neck. Thus, a rotating chair is needed to elicit proper cervical rotation while keeping the head fixed. The chair that was developed for this project was able to rotate to the specified amplitude (±0.5º of accuracy) and frequency. The parameters of the rotation amount, frequency, and amplitude can be adjusted as desired by the project guidelines. Our project aimed to improve upon existing chair models and develop a chair that can be used to assess the COR in neck pain populations.

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)0.004
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.081
GPT teacher head0.289
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 designBench or experimental
Domainnot available
GenreMethods

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
Published2021
Admission routes1
Has abstractyes

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