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Record W3141011633 · doi:10.3174/ajnr.a6120

The Interpeduncular Angle: A Practical and Objective Marker for the Detection and Diagnosis of Intracranial Hypotension on Brain MRI

2019· article· en· W3141011633 on OpenAlex
David Wang, Sachin Pandey, D.H. Lee, Manas Sharma

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2019
Typearticle
Languageen
FieldMedicine
TopicNeurosurgical Procedures and Complications
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineIntracranial HypotensionMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Classic findings of intracranial hypotension on MR imaging, such as brain stem slumping, can be variably present and, at times, subjective, potentially making the diagnosis difficult. We hypothesize that the angle between the cerebral peduncles correlates with the volume of interpeduncular cistern fluid and is decreased in cases of intracranial hypotension. We aimed to investigate its use as an objective assessment for intracranial hypotension. MATERIALS AND METHODS: test, and receiver operating characteristic analysis was used to identify an ideal angle threshold to maximize sensitivity and specificity. Interobserver reliability was assessed for classic findings of intracranial hypotension using the Cohen κ value, and the interpeduncular angle, using the intraclass correlation. RESULTS: = .01). With a threshold of 40.5°, sensitivity and specificity were 80% and 96.7%, respectively. CONCLUSIONS: The interpeduncular angle is a sensitive and specific measure of intracranial hypotension and is a reliably reproducible parameter on routine clinical MR imaging.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.153

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.286
Teacher spread0.274 · 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