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Record W2313051193 · doi:10.1017/s0317167100003000

Progress in Clinical Neurosciences: Therapeutic Hypothermia in Severe Traumatic Brain Injury

2003· review· en· W2313051193 on OpenAlexafffundvenue
David A. Zygun, Christopher Doig, Roland N. Auer, Kevin B. Laupland, Garnette R. Sutherland

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2003
Typereview
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche MédicaleBayer HealthCareWorkers' Compensation Board – AlbertaUniversity of Calgary
KeywordsHypothermiaMedicineTraumatic brain injuryIntensive care medicineClinical trialAnesthesiaPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Severe traumatic brain injury (sTBI) is a relatively common problem with few therapies proven effective. Despite its use for over 50 years, therapeutic hypothermia has not gained widespread acceptance in the treatment of sTBI due to conflicting results from clinical trials. This review will summarize the current evidence from animal, mechanistic and clinical studies supporting the use of therapeutic hypothermia. In addition, issues of rewarming and optimal temperature will be discussed. Finally, the future of hypothermia in sTBI will be addressed.

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)0.016
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.506
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.005
Science and technology studies0.0010.013
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0010.005
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 head0.148
GPT teacher head0.409
Teacher spread0.261 · 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
GenreReview

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

Citations5
Published2003
Admission routes3
Has abstractyes

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