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Record W2585949731 · doi:10.1017/cjn.2016.434

Aneurysm Tears Caused by an Aneurysm Clip Springing from the Clip Applier

2017· article· en· W2585949731 on OpenAlexvenueno aff
Yasuo Murai, Kazutaka Shirokane, Takao Kitamura, Fumihiro Matano, Akio Morita

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2017
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsAneurysmMedicineSurgeryAccidentalComplicationCLIPSRadiology

Abstract

fetched live from OpenAlex

We experienced two cases in which aneurysm clips sprang from the applier. In case 1, a subdural haematoma from a ruptured anterior cerebral artery aneurysm was detected. When the clip was opened for final positioning, it suddenly sprang from the applier and ruptured the aneurysm. In case 2, the clip suddenly sprang from the applier as the surgeon opened the applier to clip an unruptured anterior cerebral aneurysm. These accidental phenomena are rare but dangerous. We present these cases to help prevent similar occurrences in the future. Video recordings of actual procedures can point to potential mechanisms and help reduce the incidence of this complication.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.286
Teacher spread0.246 · 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 designCase report
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

Citations1
Published2017
Admission routes1
Has abstractyes

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