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Record W2592104788 · doi:10.1097/rmr.0000000000000122

ASPECTS CT in Acute Ischemia

2017· review· en· W2592104788 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTopics in Magnetic Resonance Imaging · 2017
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMagnetic resonance imagingRadiologyComputed tomographyStroke (engine)Middle cerebral arteryIschemiaIntracerebral hemorrhageSurgeryCardiologyGlasgow Coma Scale

Abstract

fetched live from OpenAlex

The Alberta Stroke Program Early CT score (ASPECTS) is a 10-point semiquantitative topographic scoring system developed for the assessment of early ischemic changes (EICs) on noncontrast-enhanced computed tomography (NCCT) in patients with acute ischemic stroke involving the middle cerebral artery (MCA) territory. One point is subtracted from a total score of 10, if an EIC is present in any part of each of the ASPECTS regions. Higher ASPECTS has been associated with better outcomes and a lower risk of symptomatic intracerebral hemorrhage. To date, there are still controversies regarding the utility of ASPECTS for selecting patients for intravenous and intra-arterial therapies. This article provides a comprehensive review regarding methodology, limitations, and interobserver reproducibility of ASPECTS, as well as application of ASPECTS in clinical care. The focus of this review is ASPECTS evaluation on NCCT. The application of ASPECTS on multimodal computed tomography and magnetic resonance imaging (MRI) is briefly described.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.356
Teacher spread0.317 · 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