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Record W1839056917 · doi:10.1152/jn.2001.86.4.1877

Neural and Mechanical Factors in Eye Control

2001· article· en· W1839056917 on OpenAlexaff
H. Misslisch, Douglas Tweed

Bibliographic record

VenueJournal of Neurophysiology · 2001
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsYork UniversityUniversity of TorontoCanadian Institutes of Health Research
Fundersnot available
KeywordsPulleyKinematicsVestibulo–ocular reflexEye movementReflexTorsion (gastropod)PhysicsComputer scienceAnatomyPsychologyClassical mechanicsArtificial intelligenceNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Soft tissue "pulleys" in the orbit alter the paths of the eye muscles in a way that may simplify the brain's work in implementing Listing's law, i.e., in holding ocular torsion at zero. But Listing's law does not apply to some oculomotor systems, such as the vestibuloocular reflex (VOR), which shows a different kinematic pattern. To explain this different pattern, some authors have assumed that the pulleys must adopt a different configuration, retracting along their muscles when the eye switches from Listing's law to VOR mode. The proposed retraction has not so far been observed, although the pulleys do move in other ways. We show that the hypothetical retraction of the pulleys would not in fact explain the full kinematic pattern seen in the VOR. But this pattern can be explained entirely on the basis of pulley positions and motions that have actually been observed. If one takes into account the neural processing within the VOR, specifically the fact that the reflex is weak in the torsional dimension, then a single mode of pulley action can serve both vestibuloocular kinematics and Listing's law.

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)0.001
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: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.022
GPT teacher head0.268
Teacher spread0.246 · 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

Citations53
Published2001
Admission routes1
Has abstractyes

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