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Record W2184045051

Non-contrast Computed Tomography in Acute Ischaemic Stroke: A Pictorial Review.

2013· article· en· W2184045051 on OpenAlexaboutno aff
Sharis Osman Syazarina, M M Shahizon Azura, H Hilwati, Muda Sobri

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombolysisAcute strokeStroke (engine)Contrast (vision)Ischaemic strokeComputed tomographyRadiologyIschemiaCardiologyInternal medicineArtificial intelligenceTissue plasminogen activatorMyocardial infarction
DOInot available

Abstract

fetched live from OpenAlex

Non-contrast computed tomography (NCCT) remains a widely used imaging technique and plays an important role in the evaluation of patients with acute ischaemic stroke. However, the task of identifying the signs of acute ischaemia and quantifying areas of brain involvement on NCCT scan is not easy due to its subtle findings. The reliability of early ischemic sign detection can be improved with experience, clinical history and the use of stroke window width and level on viewing the images. The Alberta Stroke Program Early CT Score (ASPECTS) was developed to overcome the difficulty of volume estimation in patients eligible for thrombolysis. It is a systematic, robust and practical method that can standardized the detection and reporting of the extent of acute ischaemic stroke. This article serves as an educational material that illustrates those findings which are important for all clinicians involved in acute stroke care.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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 designNot applicable
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

Citations17
Published2013
Admission routes1
Has abstractyes

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