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Record W2009481821 · doi:10.3941/jrcr.v6i9.1002

Supine Digital Subtraction Myelography for the Demonstration of a Dorsal Cerebrospinal Fluid Leak in a Patient with Spontaneous Intracranial Hypotension: A Technical Note

2012· article· en· W2009481821 on OpenAlexaff
Michael Carstensen, Navjot Chaudhary, Andrew Leung, Wai Pui Ng

Bibliographic record

VenueJournal of Radiology Case Reports · 2012
Typearticle
Languageen
FieldMedicine
TopicNeurosurgical Procedures and Complications
Canadian institutionsUniversity Hospital
Fundersnot available
KeywordsMedicineMyelographySupine positionCerebrospinal fluidLeakCerebrospinal fluid leakIntracranial HypotensionAnesthesiaProne positionSubtractionDorsumLumbar punctureRadiologySpinal cordAnatomyPathology

Abstract

fetched live from OpenAlex

A patient with spontaneous intracranial hypotension due to a spinal cerebrospinal fluid (CSF) leak required localization of the leakage site prior to surgical management. Conventional, computed tomography and prone digital subtraction myelography failed to localize the dural tear, which was postulated to be dorsally located. We present here a digital subtraction myelographic approach to accurately localize a dorsal site of CSF leakage by injecting iodinated contrast via a lumbar drain with the patient in the supine position.

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)0.003
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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