MétaCan
Menu
Back to cohort
Record W2767664257 · doi:10.28984/drhj.v1i0.22

Neurological Assessment in the Acute Care Practice Environment of Northern Ontario Hospitals

2017· article· en· W2767664257 on OpenAlexaffvenueabout
Yvonne St-Denis, Elizabeth Wenghofer, Nancy L. Young, Ellen Ruckholm

Bibliographic record

VenueDiversity of Research in Health Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsLaurentian University
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleTraumatic brain injuryIntensive care medicineNeurological examinationVital signsEmergency medicinePsychiatrySurgery

Abstract

fetched live from OpenAlex

Traumatic brain injury (TBI) is a leading cause of death and disability in developed countries and in Ontario. Trauma is the primary cause of neurological injury contributing to disability and loss of productive years. Neurological assessment remains the cornerstone to identifying evolving injury and planning care. A comprehensive assessment including all components related to neurological function, such as Glasgow Coma Scale (GCS), pupillary size and light reactivity, limb strength and vital signs, is paramount if the nurse is to initiate prompt action by medical personnel meant to improve survival outcomes and minimize long term sequelae. Clinical surveillance is essential in the identification of physiological changes and is vital in deciding whether computerized tomography (CT) is necessary. This is especially important in regions where a return trip for diagnostic testing can extend the length of time in reaching a medical diagnosis and treatment.
 Recent studies have indicated gaps in the documentation of neurological assessment. Numerous studies have examined factors that influence patient outcomes following TBI, few have looked at the short term outcomes of immediate care for mild TBI and none could be found to suggest on-going clinical surveillance provided in the first six hours contributed to positive or negative outcomes.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.125
GPT teacher head0.427
Teacher spread0.303 · 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.

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

Citations0
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueDiversity of Research in Health JournalSame topicTraumatic Brain Injury and Neurovascular DisturbancesFrench-language works237,207