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Record W2062762472 · doi:10.1097/mao.0000000000000771

Subjective Visual Vertical Tilt Attraction to the Side of Rod Presentation

2015· article· en· W2062762472 on OpenAlexaff
Michel Toupet, Christian Van Nechel, Alexis Bozorg Grayeli

Bibliographic record

VenueOtology & Neurotology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsClinique Neuro-Outaouais
Fundersnot available
KeywordsMedicineVestibular systemTilt (camera)AudiologyProspective cohort studySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to evaluate the effect of initial rod position on the subjective visual vertical (SVV) tilt and to investigate the effect of sex and age on the SVV tilt induced by this initial position. STUDY DESIGN: Prospective cross-sectional study. SETTING: Tertiary referral center. PATIENTS: The study included 6598 consecutive patients with a large range of vestibular disorders and 333 control subjects. The mean age was 55 years (range, 3-97), and the sex ratio was 0.6. INTERVENTION: SVV was measured by presenting a phosphorescent rod 12 times in total darkness with a 45-degree deviation from the vertical alternatively on the right and left. The patient was asked to replace the bar vertically with a remote control. RESULTS: On average, SVV at each iteration was tilted to the side of the rod presentation. It was stronger in female subjects, in younger individuals (<20 years) and seniors (>50). It was also higher in patients with a left vestibular loss in comparison to those with a right involvement. CONCLUSIONS: These effects suggest that short-term visual memory and multisensory cortical processing interfere with SVV measurements.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.051
GPT teacher head0.340
Teacher spread0.289 · 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

Citations20
Published2015
Admission routes1
Has abstractyes

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