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Record W7002304543

Neurosurgical Outcomes in patients with Multiple Sclerosis related Trigeminal Neuralgia

2016· other· en· W7002304543 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typeother
Languageen
FieldComputer Science
TopicData Analysis with R
Canadian institutionsnot available
Fundersnot available
KeywordsTrigeminal neuralgiaMicrovascular decompressionNeurosurgeryRhizotomyMultiple sclerosisReferralRefractory (planetary science)
DOInot available

Abstract

fetched live from OpenAlex

Trigeminal neuralgia (TN) is a cranial nerve disorder that causes intense and debilitating unilateral facial pain. Medical therapy is usually initially effective to alleviate the pain, however, approximately 1/3 to 1/2 of sufferers will eventually become refractory to medications. Surgical interventions are then available including microvascular decompression (MVD) surgery or a variety of rhizotomy techniques. The Winnipeg Centre for Cranial Nerve Disorders (wCCND) at the Health Sciences Centre is a nationally recognized referral centre for the surgical treatment of TN. Referrals for surgery are received here form across Canada as well as providing the exclusive care to Manitobans. The aim of this project will be to review the data from existing prospectively maintained clinical database of all patients (in-province and out-of-province) who underwent first time surgery for medically refractory TN at the wCCND between 2001-2015. In addition, the B.Sc. Med Student will assess most recent long-term surgical outcome data obtained through telephone interviews or clinic visits. The results will analyze and compare long-term outcomes for MVD and rhizotomies surgeries for TN. The anticipated number of patients to be included in this review is approximately 300. The B.Sc. Med student is expected to gain expertise in cranial nerve disorders that will be fostered with mentorship exposure in the neurosurgery clinic, ward, and operating room in addition to literature review and research activities.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.013
GPT teacher head0.181
Teacher spread0.168 · 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 teacher head, not a consensus.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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