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Record W2056897630 · doi:10.1002/ana.10252

Working memory after traumatic brain injury in children

2002· article· en· W2056897630 on OpenAlexaff
Harvey S. Levin, Gerri Hanten, Chung‐Chi Chang, Lifang Zhang, Russell Schachar, Linda Ewing‐Cobbs, Jeffrey E. Max

Bibliographic record

VenueAnnals of Neurology · 2002
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsHospital for Sick Children
FundersNational Institute of Neurological Disorders and Stroke
KeywordsTraumatic brain injuryWorking memoryRhymeTask (project management)PsychologyMedicineAudiologyCognitionNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

To investigate the effects of traumatic brain injury on working memory in children, we administered semantic (letter identity) and phonological (letter rhyme) N-back tasks to children who were on average 5 years post-mild (n = 54) or -severe (n = 26) traumatic brain injury and 44 typically developing children who were comparable in age. The correct detection of targets and false alarms were measured for each task. Memory load (which varied from 0 to 3 letters back) and age significantly affected the detection of targets and false alarms in both tasks. The severity of traumatic brain injury affected the correct detection of letters on the identity task and false alarms on the rhyme task. Traumatic brain injury severity also interacted with memory load in its effect on false alarms on the rhyme task. Traumatic brain injury results in impaired working memory and diminished inhibition in children. The N-back working memory task is feasible for administration to brain-injured children and potentially could be useful for studying brain activation associated with working memory and effects of drug therapy in this group of patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.162
GPT teacher head0.375
Teacher spread0.213 · 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 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

Citations109
Published2002
Admission routes1
Has abstractyes

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