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Record W1965882231 · doi:10.1159/000108011

Genes and Cerebral Ischemia Therapeutic Perspectives

2007· article· en· W1965882231 on OpenAlexaff
Kazushi Matsushima, Rainald Schmidt‐Kastner, Antoine M. Hakim

Bibliographic record

VenueCerebrovascular Diseases · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineIschemiaBrain ischemiaStroke (engine)CardiologyInternal medicine

Abstract

fetched live from OpenAlex

Research into the causes of ischemic damage has evolved into an exploration of the brain's molecular responses. In attempting to discover the specific mechanisms by which ischemic cells die, a number of protective responses which are used by the cells to prolong or assure survival have also been understood, and some of these may become useful therapeutic tools. In this limited review, the mechanisms that are most likely to play a role in determining whether an ischemic cell survives or not are identified and examined. Particular emphasis is placed on the role of immediate early genes, heat shock proteins and trophic factors, and the more recent suspicion that cell cycle genes may be involved in the process of death by apoptosis. As well, the possibility that spreading depression may be a tool that may permit a better understanding of some of these mechanisms as well as offer new therapeutic avenues is examined.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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 designBench or experimental
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

Citations8
Published2007
Admission routes1
Has abstractyes

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