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Record W3120261134 · doi:10.1038/s41598-020-79540-3

An atlas for human brain myelin content throughout the adult life span

2021· article· en· W3120261134 on OpenAlexafffund
Adam Dvorak, Taylor Swift-LaPointe, Irene M. Vavasour, Lisa Eunyoung Lee, Shawna Abel, Bretta Russell‐Schulz, Carina Graf, Anika Wurl, Hanwen Liu, Cornelia Laule, David K.B. Li, Anthony Traboulsee, Roger Tam, Lara A. Boyd, Alex L. MacKay, Shannon Kolind

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersMultiple Sclerosis SocietyNatural Sciences and Engineering Research Council of CanadaVancouver Coastal Health Research InstituteMultiple Sclerosis Society of CanadaMichael Smith Health Research BC
KeywordsMyelinNeuroimagingContext (archaeology)White matterContent (measure theory)BiologyLife spanNeuroscienceMagnetic resonance imagingMedicineEvolutionary biologyCentral nervous systemMathematics

Abstract

fetched live from OpenAlex

Abstract Myelin water imaging is a quantitative neuroimaging technique that provides the myelin water fraction (MWF), a metric highly specific to myelin content, and the intra-/extra-cellular T2 (IET2), which is related to water and iron content. We coupled high-resolution data from 100 adults with gold-standard methodology to create an optimized anatomical brain template and accompanying MWF and IET2 atlases. We then used the MWF atlas to characterize how myelin content relates to demographic factors. In most brain regions, myelin content followed a quadratic pattern of increase during the third decade of life, plateau at a maximum around the fifth decade, then decrease during later decades. The ranking of mean myelin content between brain regions remained consistent across age groups. These openly available normative atlases can facilitate evaluation of myelin imaging results on an individual basis and elucidate the distribution of myelin content between brain regions and in the context of aging.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0130.004

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 head0.130
GPT teacher head0.415
Teacher spread0.285 · 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

Citations81
Published2021
Admission routes2
Has abstractyes

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