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Record W2071865073 · doi:10.1080/13803395.2011.645016

A short bedside battery for visuoconstructive hemispatial neglect: Sunnybrook Neglect Assessment Procedure (SNAP)

2012· article· en· W2071865073 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical and Experimental Neuropsychology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsUniversity of TorontoHealth Sciences CentreHeart and Stroke FoundationSunnybrook Health Science Centre
Fundersnot available
KeywordsHemispatial neglectNeglectPsychologyStroke (engine)PopulationRehabilitationPhysical medicine and rehabilitationPsychiatryClinical psychologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

Although it is currently not known whether early assessment and treatment of hemispatial neglect improves rehabilitation outcome, identification in the acute phase of post stroke is important for nursing, counseling families, and planning intervention strategies. Previous tests of neglect either fail to detect mild forms of neglect or are too lengthy for use at the bedside. We tested and selected an efficient, small battery of tests to address this gap. Two hundred and twenty-four stroke patients completed the Sunnybrook Neglect Assessment Procedure (SNAP). Normal performance was determined from a population of 100 normal elderly volunteers. The SNAP was shown to be a highly reliable and valid instrument. Factor analysis showed good internal consistency, suggesting that performance on each subtest is positively correlated with the others. The SNAP is a useful and reliable tool to assess neglect at the bedside in acute stroke patients.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.063
GPT teacher head0.424
Teacher spread0.360 · 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