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Record W2023328588 · doi:10.1212/wnl.0b013e31821ccd4f

Looking into posterior cortical atrophy

2011· letter· en· W2023328588 on OpenAlexaff
David F. Tang‐Wai, Neill R. Graff‐Radford

Bibliographic record

VenueNeurology · 2011
Typeletter
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsPosterior cortical atrophyAtrophyNeuroscienceDiseaseAlzheimer's diseaseMedicinePsychologyPathologyDementia

Abstract

fetched live from OpenAlex

Posterior cortical atrophy (PCA) is a dementing syndrome that presents with signs and symptoms of cortical visual dysfunction.1 The clinical features of PCA reflect dysfunction mainly of the dorsal/occipito-parietal pathway causing Balint syndrome (simultanagnosia, optic ataxia, and ocular apraxia), transcortical sensory aphasia, apraxia, and some or all elements of Gerstmann syndrome (agraphia, acalculia, finger agnosia, right-left disorientation).1,2 Formal neuropsychological testing has confirmed a relative greater impairment of dorsal visual stream function while frontal lobe functions and memory are relatively preserved until later in the course of the disease.2 Structural and functional neuroimaging has consistently revealed atrophy or metabolic changes in the posterior regions of the brain.3 Although PCA is a clinically homogeneous syndrome, there is pathologic heterogeneity. Corticobasal degeneration, dementia with Lewy bodies, subcortical gliosis, fatal familial insomnia, and Creutzfeldt-Jacob disease have all been described as causing PCA.1,4 However, the most common reported pathologic cause is Alzheimer disease (AD) with increased density of neurofibrillary …

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: Case report · Consensus signal: Case report
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.239
Teacher spread0.217 · 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 designCase report
Domainnot available
GenreCommentary

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

Citations9
Published2011
Admission routes1
Has abstractyes

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