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Record W3140314054 · doi:10.4021/jnr236w

Level Diagnosis of Cervical Compressive Myelopathy: Signs, Symptoms, and Lesions Levels

2013· article· en· W3140314054 on OpenAlexvenueno aff
Kasahata

Bibliographic record

VenueJournal of Neurology Research · 2013
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHyperreflexiaMyelopathyMagnetic resonance imagingBicepsSpondylolysisBrachioradialisReflexRadiologyAnatomyLumbarSurgerySpinal cordInternal medicine

Abstract

fetched live from OpenAlex

Background: To elucidate signs and symptoms corresponding to each vertebral level for level-specific diagnoses. Methods: We studied 106 patients with cervical compressive myelopathy. Patients who showed a single compressive site on magnetic resonance imaging ( MRI ) were selected, and signs, symptoms, and the levels of the MRI lesions were studied. Results: Five of 12 patients (41.7%) with C4-5 intervertebral level lesions showed decreased or absent biceps and brachioradialis reflexes, while 4 of these patients (33.3%) showed generalized hyperreflexia. In comparison, 5 of 24 patients (20.8%) with C5-6 intervertebral level lesions showed decreased or absent triceps reflexes; however, 9 of these patients (37.5%) showed decreased or absent biceps and brachioradialis reflexes. Conclusions: C4-5 intervertebral level lesions not only showed C6 segment signs but also showed more rostral segment signs. Similarly, C5-6 intervertebral level lesions not only showed C7 segment signs but also showed C6 or more rostral segment signs. J Neurol Res. 2013;3(5):135-141 doi: https://doi.org/10.4021/jnr236w

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.161
GPT teacher head0.398
Teacher spread0.237 · 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 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

Citations1
Published2013
Admission routes1
Has abstractyes

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Same venueJournal of Neurology ResearchSame topicCervical and Thoracic MyelopathyFrench-language works237,207