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Record W3109992576 · doi:10.3390/brainsci10120930

Covert Cognition in Disorders of Consciousness: A Meta-Analysis

2020· article· en· W3109992576 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrain Sciences · 2020
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPersistent vegetative stateCovertNeuroimagingMinimally conscious stateMeta-analysisConsciousness DisordersCognitionPsychologyObservational studyFunctional neuroimagingSample size determinationConsciousnessCognitive psychologyClinical psychologyMedicineNeurosciencePathology

Abstract

fetched live from OpenAlex

Covert cognition in patients with disorders of consciousness represents a real diagnostic conundrum for clinicians. In this meta-analysis, our main objective was to identify clinical and demographic variables that are more likely to be associated with responding to an active paradigm. Among 2018 citations found on PubMed, 60 observational studies were found relevant. Based on the QUADAS-2, 49 studies were considered. Data from 25 publications were extracted and included in the meta-analysis. Most of these studies used electrophysiology as well as counting tasks or mental imagery. According to our statistical analysis, patients clinically diagnosed as being in a vegetative state and in a minimally conscious state minus (MCS-) show similar likelihood in responding to active paradigm and responders are most likely suffering from a traumatic brain injury. In the future, multi-centric studies should be performed in order to increase sample size, with similar methodologies and include structural and functional neuroimaging in order to identify cerebral markers related to such a challenging diagnosis.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.239
GPT teacher head0.406
Teacher spread0.166 · 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