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Record W2001475029 · doi:10.1097/wnr.0b013e32820049bd

Deficits in peripheral visual attention in patients with optic ataxia

2007· article· en· W2001475029 on OpenAlexafffund
Christopher L. Striemer, Annabelle Blangero, Yves Rossetti, Dominique Boisson, Gilles Rode, Alain Vighetto, Laure Pisella, James Danckert

Bibliographic record

VenueNeuroreport · 2007
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsPsychologyAtaxiaSalience (neuroscience)Visual fieldNeurosciencePeripheralAudiologyPeripheral visionVisual perceptionVisual attentionPerceptionCognitive psychologyMedicine

Abstract

fetched live from OpenAlex

Earlier research has suggested that optic ataxia, a deficit in reaching in peripheral vision, can be isolated from Balint's syndrome as it is primarily a visuomotor disorder, independent of perceptual or attentional deficits. Yet almost no research has examined the attentional abilities of these patients. We examined peripheral visual attention in two patients with unilateral optic ataxia. Results indicated that both patients were slower to respond to targets in their ataxic visual field, irrespective of cuing condition (i.e. validly, invalidly, and no cue conditions), consistent with an overall decrease in the salience of stimuli in the ataxic field. Attentional deficits in peripheral vision are therefore an important factor to consider when examining visuomotor control deficits in optic ataxia.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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 designObservational
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

Citations49
Published2007
Admission routes2
Has abstractyes

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