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Record W4388653991 · doi:10.7202/1076466ar

Nurses’ Evaluations of the Feasibility and Clinical Utility of the Use of the Critical-Care Pain Observation Tool-Neuro in Critically Ill Brain-Injured Patients

2019· article· en· W4388653991 on OpenAlexafffundvenue
Mélissa Richard-Lalonde, Mélanie Berube, Virginie Williams, Françis Bernard, Darina M. Tsoller, Céline Gélinas

Bibliographic record

VenueScience of Nursing and Health Practices · 2019
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsJewish General HospitalHôpital du Sacré-Cœur de MontréalUniversité LavalMcGill University
FundersCanadian Institutes of Health Research
KeywordsMedicineCritically illIntensive care unitIntensive care medicineBrain traumaIntensive careClinical PracticeTraumatic brain injuryNursingPsychiatry

Abstract

fetched live from OpenAlex

Nurses’ Evaluations of the Feasibility and Clinical Utility of the Use of the Critical-Care Pain Observation Tool-Neuro in Critically Ill Brain-Injured Patients. Un article de la revue Science of Nursing and Health Practices / Science infirmière et pratiques en santé (Volume 2, numéro 2, 2019) diffusée par la plateforme Érudit.

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)0.316
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science 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 score0.312
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.316
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.319
GPT teacher head0.535
Teacher spread0.215 · 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

Citations1
Published2019
Admission routes3
Has abstractyes

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