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Record W2066276013 · doi:10.1155/2012/143705

Characterization of DTI Indices in the Cervical, Thoracic, and Lumbar Spinal Cord in Healthy Humans

2012· article· en· W2066276013 on OpenAlexafffund
Rachael L. Bosma, Patrick W. Stroman

Bibliographic record

VenueRadiology Research and Practice · 2012
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsInternational Spinal Research Trust
KeywordsMedicineLumbarSpinal cordAnatomyThoracic vertebraeLumbar vertebrae

Abstract

fetched live from OpenAlex

The aim of this study was to characterize in vivo measurements of diffusion along the length of the entire healthy spinal cord and to compare DTI indices, including fractional anisotropy (FA) and mean diffusivity (MD), between cord regions. The objective is to determine whether or not there are significant differences in DTI indices along the cord that must be considered for future applications of characterizing the effects of injury or disease. A cardiac gated, single-shot EPI sequence was used to acquire diffusion-weighted images of the cervical, thoracic, and lumbar regions of the spinal cord in nine neurologically intact subjects (19 to 22 years). For each cord section, FA versus MD values were plotted, and a k-means clustering method was applied to partition the data according to tissue properties. FA and MD values from both white matter (average FA = 0.69, average MD = 0.93 × 10(-3) mm(2)/s) and grey matter (average FA = 0.44, average MD = 1.8 × 10(-3) mm(2)/s) were relatively consistent along the length of the cord.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.308
GPT teacher head0.552
Teacher spread0.244 · 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

Citations15
Published2012
Admission routes2
Has abstractyes

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