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Record W1582179550 · doi:10.1089/neu.2015.3965

The Role of Thalamic Damage in Mild Traumatic Brain Injury

2015· review· en· W1582179550 on OpenAlexfundno aff
Elan J. Grossman, Matilde Inglese

Bibliographic record

VenueJournal of Neurotrauma · 2015
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
FundersNational Institutes of HealthNational Institute of Neurological Disorders and StrokeSchool of Medicine, New York UniversityYork University
KeywordsNeuroscienceWhite matterTraumatic brain injuryThalamusDiseasePsychologyBrain damageMedicineMagnetic resonance imagingPsychiatryPathologyRadiology

Abstract

fetched live from OpenAlex

There is growing alarm in the United States about an epidemiologically large occurrence of mild traumatic brain injury with serious long lasting consequences. Although conventional imaging has been unable to identify damage capable of explaining its organic origin or discerning patients at risk of developing long-term or permanently disabling neurological impairment, most disease models assume that diffuse axonal injury in white matter must be present but is difficult to resolve. The few histopathological investigations conducted, however, show only limited evidence of such damage, which cannot account for the stereotypical globalized nature of symptoms generally reported in patients. This review examines recent proposals that in addition to white matter, the thalamus may be another important further site of injury. Although its possible role still remains largely under-investigated, evidence from experimental human and animal models, as well as simulational and analytical representations of mild head injury and other related conditions, suggest that this strategically vital region of the brain, which has reciprocal projections to the entire cerebral cortex, could feasibly play an important role in understanding pathology and predicting outcome.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.136
GPT teacher head0.391
Teacher spread0.255 · 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.

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

Citations78
Published2015
Admission routes1
Has abstractyes

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