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Record W2139297655 · doi:10.1080/02699050050203577

Electrophysiological evidence for the cumulative effects of concussion

2000· article· en· W2139297655 on OpenAlexaff
D. Goodman M. Gaetz

Bibliographic record

VenueBrain Injury · 2000
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsConcussionCognitionMedicineIce hockeyPhysical medicine and rehabilitationElectrophysiologyEvent-related potentialPoison controlPsychologyPhysical therapyAudiologyInjury preventionInternal medicinePsychiatryMedical emergency

Abstract

fetched live from OpenAlex

PURPOSE: A study was initiated with the intent of demonstrating the cumulative effects of concussion in junior hockey players using visual event-related potentials and post-concussion syndrome (PCS) self-reports. METHODS: Players were assessed at the beginning of the season (pre-injury) and at various times post-injury. RESULTS: The results suggest that players with three or more concussions differed significantly on the several cognitive PCS symptoms as well as for the latency of the P3 response compared to those with no concussion history. DISCUSSION: Event-related potentials are useful indices of the cumulative damage that can occur following multiple concussions. These measures correlate significantly with cognitive self-reports of PCS symptoms. CONCLUSIONS: This pattern of results is consistent with the position that each concussion potentially causes brain damage. Cumulative damage can be detected using electrophysiological measures of brain function.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.414
Teacher spread0.319 · 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

Citations227
Published2000
Admission routes1
Has abstractyes

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