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Record W2027747149 · doi:10.1097/wco.0b013e32834c7eb9

Traumatic brain injury

2011· review· en· W2027747149 on OpenAlexafffund
Donald T. Stuss

Bibliographic record

VenueCurrent Opinion in Neurology · 2011
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsBaycrest HospitalOntario Brain InstituteUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsTraumatic brain injuryEmpathyFrontal lobePsychologyRehabilitationCognitionCognitive psychologyLimitingExecutive functionsPhysical medicine and rehabilitationClinical psychologyNeuroscienceMedicinePsychiatry

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review examines the applicability of a framework of frontal lobe functioning to understand the sequelae of traumatic brain injury (TBI). RECENT FINDINGS: TBI research illustrates the need for improved phenotyping of TBI outcome. The functions of the frontal lobes are divisible into four distinct anatomically discrete categories: executive functions, speed of processing, personality changes, and problems with empathy and social cognition. Research on the outcome after TBI demonstrates several different types of impairment that map onto this framework. SUMMARY: TBI predominantly causes damage to the frontal/temporal regions, regardless of the pathophysiology. Limiting the spotlight to the frontal lobes, a model is presented describing four separate general categories of functions within the frontal lobes, with specific types of processes within each category. A selective review of TBI literature supports the importance of evaluating TBI patients with this framework in mind. In addition, there is growing evidence that rehabilitation of TBI patients must consider this broader approach to direct rehabilitation efforts and improve 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 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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.008

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 head0.432
GPT teacher head0.505
Teacher spread0.073 · 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 designNot applicable
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

Citations231
Published2011
Admission routes2
Has abstractyes

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