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Record W4399995661 · doi:10.1162/imag_a_00221

Imaging of the superficial white matter in health and disease

2024· article· en· W4399995661 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

VenueImaging Neuroscience · 2024
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsWhite matterWhite (mutation)MedicineMagnetic resonance imagingRadiologyChemistry

Abstract

fetched live from OpenAlex

The superficial white matter, the layer of white matter immediately deep to the cortical grey matter, is a highly complex, heterogeneous tissue region comprising dense meshes of neural fibres, a robust population of interstitial neurons, and ongoing glial activity and myelination. It originates from the histologically distinct, developmentally vital subplate in the foetal brain, maintains thalamo-cortical connections throughout adult life, and is a necessary passage for all axons passing between the grey and white matter. Despite these features, the superficial white matter is among the most poorly understood regions of the brain, in part due to its complex makeup and the resulting difficulty of its study. In this review, we present our current knowledge of superficial white matter (SWM) anatomy, development, and response to disease. We discuss the unique challenges encountered in the neuroimaging of this region, including the lack of standard definition and the non-specificity of neuroimaging markers amplified by the complexity of the tissue. We discuss recent innovations and offer potential pathways forward.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.383
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.357
Teacher spread0.324 · 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