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Record W4283835219 · doi:10.1161/strokeaha.122.039069

By and Large, Thrombectomy in Large Core Is a Palpable Reality

2022· article· en· W4283835219 on OpenAlexaboutno aff
Diogo C Haussen, Jens Fiehler

Bibliographic record

VenueStroke · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineModified Rankin ScalePraiseMagnetic resonance imagingStroke (engine)Metric (unit)Randomized controlled trialPhysical therapyAcute strokeSurgeryRadiologyIschemic strokeInternal medicineOperations managementNursingEmergency department

Abstract

fetched live from OpenAlex

Our Japanese colleagues deserve much praise for finishing the first randomized clinical trial of thrombectomy in Alberta Stroke Program Early CT Score 3 to 5 patients showing an impressive therapy effect of thrombectomy. The predominant use of magnetic resonance imaging for patient selection, the low rate of alteplase therapy and its low dose limit direct comparisons with patients treated outside of Japan. Another limitation is the lack of benefit when using the traditional metric-modified Rankin Scale score 0-2. We consider the results of RESCUE-Japan LIMIT encouraging and a clear motivation to continue and complete other studies.

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)0.024
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.011
Scholarly communication0.0070.020
Open science0.0030.003
Research integrity0.0120.034
Insufficient payload (model declined to judge)0.0080.007

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 head0.019
GPT teacher head0.290
Teacher spread0.271 · 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 designObservational
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

Citations3
Published2022
Admission routes1
Has abstractyes

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