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Record W2068213597 · doi:10.3171/foc.2007.22.6.6

Clinical examination of brachial and pelvic plexus tumors

2007· review· en· W2068213597 on OpenAlexaff
Shelly Lwu, Rajiv Midha

Bibliographic record

VenueNeurosurgical FOCUS · 2007
Typereview
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineAsymptomaticLesionPhysical examinationDifferential diagnosisNeurological examinationPathologicalBrachial plexusNeurofibromatosisSensory systemMedical historyPathologyRadiologySurgeryNeurosciencePsychology

Abstract

fetched live from OpenAlex

A thorough history and physical examination are fundamental to the assessment of patients with brachial and pelvic plexus tumors. Typical of most peripheral nerve tumors, the presenting symptoms and signs are few, and if present, can be subtle. Presenting complaints may include a palpable mass lesion, either symptomatic or asymptomatic; sensory alterations; pain; motor deficits; visceral symptoms; or autonomic dysfunction. Motor deficits are usually a late feature in the pathogenesis of this lesion, and a progressive course of pain and significant sensory and motor deficits suggests a malignant pathological process. A detailed family history may reveal familial syndromes and neurocutaneous disorders that predispose the patient to neoplasia, such as neurofibromatosis. The physical examination should be conducted in a systematic fashion, looking for any cutaneous features and motor and sensory deficits. The mass should also be examined for form, consistency, and mobility. An irregular, firm, and immobile mass suggests a malignant lesion. Complete and accurate clinical information must be gathered to pinpoint the anatomical localization of the lesion and formulate a differential diagnosis.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.104
GPT teacher head0.394
Teacher spread0.290 · 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 designOther design
Domainnot available
GenreReview

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

Citations15
Published2007
Admission routes1
Has abstractyes

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