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Record W2606276801 · doi:10.1007/s00586-017-5097-4

A prospective serial MRI study following acute traumatic cervical spinal cord injury

2017· article· en· W2606276801 on OpenAlexafffund
Joost Rutges, Brian K. Kwon, Manraj K. S. Heran, Tamir Ailon, John Street, Marcel F. Dvorak

Bibliographic record

VenueEuropean Spine Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsVancouver General HospitalInternational Collaboration On Repair DiscoveriesVancouver Spine Surgery InstituteUniversity of British Columbia
FundersRick Hansen Institute
KeywordsMedicineSpinal cord injurySpinal cordCordHematomaNeurosurgeryEdemaMagnetic resonance imagingAnesthesiaSpinal cord compressionProspective cohort studySurgeryRadiology

Abstract

fetched live from OpenAlex

PURPOSE: In acute traumatic cervical spinal cord injury (SCI) patients, we sought to characterize how objective MRI measures of injury change during the first 3 week post-injury. METHODS: Six MRI scans each were planned in 19 cervical SCI patients within the first 3 week post-injury. Length of cord edema, maximum spinal cord compression, maximum canal compromise, and presence and length of hematoma were measured. RESULTS: Length of spinal cord edema increased in the first 48 h after SCI, followed by a gradual decrease in the 3 weeks after injury. This was predominantly seen in the more severe grades of SCI. Hematoma in the spinal cord was seen in all AIS-A and B patients. CONCLUSION: This study demonstrates the dynamic nature of imaging changes on MRI in the first weeks after injury and highlights the importance of taking into account the timing of imaging when interpreting objective measures of damage.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.067
GPT teacher head0.427
Teacher spread0.361 · 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

Citations52
Published2017
Admission routes2
Has abstractyes

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