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Record W3202587163 · doi:10.1080/21507740.2021.1973148

Frequent Preservation of Neurologic Function in Brain Death and Brainstem Death Entails False-Positive Misdiagnosis and Cerebral Perfusion

2021· article· en· W3202587163 on OpenAlexaff
Michael Nair‐Collins, Ari R. Joffe

Bibliographic record

VenueAJOB Neuroscience · 2021
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsStollery Children's HospitalUniversity of Alberta
Fundersnot available
KeywordsBrainstemBrain functionNeuroscienceMedicinePsychology

Abstract

fetched live from OpenAlex

Some patients who have been diagnosed as "dead by neurologic criteria" continue to exhibit certain brain functions, most commonly, neuroendocrine functions. This preservation of neurologic function after the diagnosis of "brain death" or "brainstem death" is an ongoing source of controversy and concern in the medical, bioethics, and legal literatures. Most obviously, if some brain function persists, then it is not the case that all functions of the entire brain have ceased and hence, declaring such a patient to be "dead" would be a false positive, in any nation with so-called "whole brain death" laws. Furthermore, and perhaps more concerning, the preservation of any brain function necessarily entails the preservation of some amount of brain perfusion, thereby raising the concern as to whether additional areas of neural tissue may remain viable, including areas in the brainstem. These and other considerations cast significant doubt on the reliability of diagnosing either "brain death" or "brainstem death."

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)0.015
metaresearch head score (Gemma)0.059
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 score0.015
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.006
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.271
Teacher spread0.242 · 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

Citations46
Published2021
Admission routes1
Has abstractyes

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