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Record W2471677761 · doi:10.1080/00222895.2015.1134436

Fitts’ Theorem in Oculomotor Control: Dissociable Movement Times for Amplitude and Width Manipulations

2016· article· en· W2471677761 on OpenAlexaff
Matthew Heath, Ashna Samani, Luc Tremblay, Digby Elliott

Bibliographic record

VenueJournal of Motor Behavior · 2016
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcMaster UniversityUniversity of TorontoWestern University
Fundersnot available
KeywordsAmplitudeKinematicsSaccadeMathematicsUnitary stateMovement (music)Mathematical analysisConstant (computer programming)Control theory (sociology)CommunicationPhysicsEye movementPsychologyControl (management)Computer scienceClassical mechanicsOpticsNeuroscienceArtificial intelligenceAcoustics

Abstract

fetched live from OpenAlex

The authors examined whether movement times (MT) for discrete saccades are constant given equivalent index of difficulty (ID) values (i.e., unitary nature of Fitts' theorem). To that end, we contrasted ID/MT relations for saccades equated for ID but differing with respect to their target amplitudes and widths. Results showed that MT increased with increasing ID within amplitude and width conditions; however, the ID/MT slope was markedly steeper in the former condition. Thus, the amplitude condition imposed greater information processing demands than the width condition-a result indicating that the constituent elements of Fitts' theorem are dissociable (i.e., nonunitary). Further, examination of saccade kinematics demonstrated that the optimal MT for a given target amplitude was largely independent of target width.

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)0.001
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
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 science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.334
Teacher spread0.280 · 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".

Quick stats

Citations13
Published2016
Admission routes1
Has abstractyes

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