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Record W2054766524 · doi:10.4137/mri.s10692

Diffusion Tensor Metric Measurements as a Function of Diffusion Time in the Rat Central Nervous System

2012· article· en· W2054766524 on OpenAlex
Jonathan D. Thiessen, Trevor Vincent, Sheryl L. Herrera, Melanie Martin

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMagnetic Resonance Insights · 2012
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaMultiple Sclerosis Society of Canada
KeywordsGrey matterDiffusion MRIWhite matterFractional anisotropyDiffusionPhysicsThermal diffusivityAnisotropyNuclear magnetic resonanceChemistryMagnetic resonance imagingMedicineThermodynamicsOptics

Abstract

fetched live from OpenAlex

MRI and Monte Carlo simulated data of pulsed gradient spin echo experiments were used to study the effects of diffusion time, gradient strength and b-value on diffusion tensor (DT) metrics using real and simulated fixed rat spines. Radial (λ ⊥ ) in grey matter and simulation data, axial (λ || ) in both grey and white matter in fixed rat spinal cords and mean diffusivity in all tissues showed a significant decrease with diffusion time at b = 1 μm 2 /ms. All diffusivities significantly decreased with b-value at g = 116 mT/m and at Δ eff = 23 ms. The fractional anisotropy (FA) significantly increased with diffusion time at b = 1 μm 2 /ms in the simulation data and grey matter. FA significantly increased in white matter and simulation data and significantly decreased in grey matter with b-value at g = 116 mT/m and at Δ eff = 23 ms. These data suggest that DTI metrics are highly dependent on pulse sequence parameters.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.047
GPT teacher head0.286
Teacher spread0.239 · 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