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Record W2754687916 · doi:10.3390/brainsci7090119

COACH CV: The Seven Clinical Phenotypes of Concussion

2017· article· en· W2754687916 on OpenAlexaff
Neil Craton, Haitham Ali, Stéphane Lenoski

Bibliographic record

VenueBrain Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsConcussionPhenotypePsychologyMedicinePhysical medicine and rehabilitationPoison controlInjury preventionBiologyMedical emergencyGenetics

Abstract

fetched live from OpenAlex

Our understanding of the diverse physiological manifestations of concussion is changing rapidly. This has an influence on the clinical assessment of patients who have sustained a concussion. The 2017 Consensus Statement on Concussion in Sport states that numerous post-injury clinical findings, such as cognitive deficits, post-traumatic headaches, dizziness, difficulties with oculomotor function, and depression have all been associated with a poorer prognosis in concussed patients. This demonstrates that there are several potential clinical manifestations after head injury warranting clinical evaluation. We have developed an acronym to guide the office-based assessment of concussed patients to consider each of the potential clinical phenotypes. "COACH CV" prompts the clinician to evaluate for cognitive problems, oculomotor dysfunction, affective disturbances, cervical spine disorders, headaches, and cardiovascular and vestibular anomalies.

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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.296
GPT teacher head0.510
Teacher spread0.214 · 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

Citations29
Published2017
Admission routes1
Has abstractyes

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