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Record W1602207147 · doi:10.5772/28577

Diaschisis, Degeneration, and Adaptive Plasticity After Focal Ischemic Stroke

2012· book-chapter· en· W1602207147 on OpenAlexaff
Bernice Sist, Sam Joshva Baskar Jesudasan, Ian R.

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStroke (engine)MedicineThrombolysisCardiologyTissue plasminogen activatorCerebral blood flowPlasminInternal medicineSurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

adopt the function of neural tissue destroyed by ischemia (Winship and Murphy, 2009;C.E. Brown and Murphy, 2008).While pathological and adaptive changes that occur in periinfarct cortex have been well characterized, less research has examined adaptive and maladaptive changes distal to the infarct.I n t h i s c h a p t e r , w e w i l l r e v i e w t h e pathophysiology that leads to expansion of the infarct into surrounding peri-infarct tissue, diaschisis and degeneration in distal but anatomically connected regions, and the adaptive changes that occur distal to the infarct after focal stroke.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.008

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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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 designTheoretical or conceptual
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

Citations8
Published2012
Admission routes1
Has abstractyes

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