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Record W1989462236 · doi:10.1002/mrm.21527

High‐resolution myelin water measurements in rat spinal cord

2008· article· en· W1989462236 on OpenAlexaff
Piotr Kozłowski, Jie Liu, Andrew Yung, Wolfram Tetzlaff

Bibliographic record

VenueMagnetic Resonance in Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
Fundersnot available
KeywordsSpinal cordMyelinResolution (logic)Nuclear magnetic resonanceMyelin sheathChemistryNeuroscienceCentral nervous systemBiologyPhysicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Multiecho imaging data were acquired at 7T from control and injured (dorsal column transection) rat spinal cords ex vivo with in-plane resolution of 61, 78, and 100 microm, and from a control rat spinal cord in vivo with in-plane resolution of 117 microm. The myelin water maps were calculated using nonnegative least-squares (NNLS) analysis of the decay curves. For the control cords, myelin water maps showed details of the cord morphology, and the average myelin water fraction (MWF) values in white matter and gray matter corresponded well with previously published results and the expected amounts of myelin within the cord, and correlated very well with Luxol Fast Blue stain (R(2)=0.95). Myelin water maps from an injured cord showed excellent qualitative correlation with histology. This pilot study demonstrates that high-resolution myelin water mapping in rat spinal cord is feasible, and this technique has potential to be a valuable tool in studying white matter damage in rat models of spinal cord injury.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.536

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 head0.123
GPT teacher head0.360
Teacher spread0.237 · 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 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

Citations64
Published2008
Admission routes1
Has abstractyes

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