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Record W2765439860 · doi:10.1016/j.tcr.2017.10.011

Blunt innominate artery trauma requiring repair and carotid ligation

2017· article· en· W2765439860 on OpenAlexaff
Kathryn L. Howe, Mina Guirgis, Grant Woodman, F. Victor Chu, Michael Cooper, Theodore Rapanos, David Szalay

Bibliographic record

VenueTrauma Case Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicVascular Procedures and Complications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLigationMedicineDissection (medical)Context (archaeology)BluntCarotid arteriesSurgeryBlunt traumaRadiology

Abstract

fetched live from OpenAlex

Traumatic dissection of the innominate artery is a rare clinical entity. Management of a patient with motorsensory compromise and dissection extending to the subclavian and right common carotid arteries is quite rare and can be quite involved. Here we present such a case and discuss the unique peri-operative decision-making in the context of what is reported in the literature. Restoration of motorsensory function is critical and in this case, requiring a multi-disciplinary team.

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)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.032
GPT teacher head0.301
Teacher spread0.269 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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