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Record W2115284165 · doi:10.1093/brain/awu225

Does dominant pedunculopontine nucleus exist?

2014· letter· en· W2115284165 on OpenAlexaff
Susy Lam, Elena Moro, Yu‐Yan Poon, Andrés M. Lozano, Alfonso Fasano

Bibliographic record

VenueBrain · 2014
Typeletter
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsPedunculopontine nucleusDiffusion MRIParkinson's diseaseNeuroscienceLateralityPsychologyWhite matterLateralization of brain functionDiseaseMedicinePhysical medicine and rehabilitationMagnetic resonance imagingInternal medicineDeep brain stimulationRadiology

Abstract

fetched live from OpenAlex

Sir, We read with great interest the paper by Fling et al. (2013) recently published in Brain . In this imaging study, patients with Parkinson’s disease with freezing of gait (FOG), without FOG, and age-matched controls were studied with diffusion tensor imaging to identify group and inter-hemispheric differences of tract quality and quantity in the pedunculopontine nucleus (PPN) network. Interestingly, patients with Parkinson’s disease with FOG had significantly less right PPN tract volume in terms of absolute values and ratio with the left side (i.e. greater laterality index) compared to patients without FOG. Furthermore, solely in the Parkinson’s disease with FOG group, linear regression analysis significantly correlated greater lateralization of PPN tract volume with poorer performance in action inhibition tasks. The authors concluded that right hemispheric circuitry might be uniquely involved in the pathophysiology of FOG (Fling et al. , 2013). In keeping with these findings, clinical evidence from the DATATOP cohort supports the notion …

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.059
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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 designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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