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Record W2807990765 · doi:10.1089/neu.2018.5935

A Review of Clinical Trials in Spinal Cord Injury Including Biomarkers

2018· review· en· W2807990765 on OpenAlexaff
Jetan H. Badhiwala, Jefferson R. Wilson, Brian K. Kwon, Steven Casha, Michael G. Fehlings

Bibliographic record

VenueJournal of Neurotrauma · 2018
Typereview
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of CalgaryVancouver Spine Surgery InstituteUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsClinical trialMedicineSpinal cord injuryRandomized controlled trialIntensive care medicinePhysical therapySpinal cordSurgeryPathologyPsychiatry

Abstract

fetched live from OpenAlex

Acute traumatic spinal cord injury (SCI) entered the arena of prospective, randomized clinical trials almost 40 years ago, with the undertaking of the National Acute Spinal Cord Study (NASCIS) I trial. Since then, a number of clinical trials have been conducted in the field, spurred by the devastating physical, social, and economic consequences of acute SCI for patients, families, and society at large. Many of these have been controversial and attracted criticism. The current review provides a critical summary of select past and current clinical trials in SCI, focusing in particular on the findings of prospective, randomized controlled trials, the challenges and barriers encountered, and the valuable lessons learned that can be applied to future trials.

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)0.048
metaresearch head score (Gemma)0.060
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0480.060
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0130.005
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.772
GPT teacher head0.674
Teacher spread0.097 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations54
Published2018
Admission routes1
Has abstractyes

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