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Record W1955664833 · doi:10.1002/ajpa.22730

Does the correlation between schmorl's nodes and vertebral morphology extend into the lumbar spine?

2015· article· en· W1955664833 on OpenAlexafffund
Kimberly A. Plomp, Charlotte A. Roberts, Una Strand Viðarsdóttir

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2015
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsSimon Fraser University
FundersMitacsSimon Fraser UniversityDurham University
KeywordsAnatomyMedicineLumbar vertebraeLumbarLumbar spineIntervertebral discThoracic vertebraeVertebral bodySurgery

Abstract

fetched live from OpenAlex

Schmorl's nodes are depressions on vertebrae due to herniation of the nucleus pulposus of the intervertebral disc into the vertebral body. This study provides an extension of our previous study which analyzed the shape of the lower thoracic spine and found that vertebral morphology was associated with the presence of Schmorl's nodes. Ninety adult individuals from the late Medieval site of Fishergate House, York, and the Post-Medieval site of Coach Lane, North Shields, Tyne and Wear, England, were analysed using 2D geometric morphometrics to identify possible relationships between vertebral morphology and Schmorl's nodes at the thoraco-lumbar junction and in the lumbar spine. A significant correlation was found between vertebral shape and the presence of Schmorl's nodes in the twelfth thoracic vertebrae and the first to third lumbar vertebrae. The findings corroborate previous studies and suggest that vertebral shape may be an important factor in spinal health. It is hypothesized that the pedicle shape of affected vertebrae may not provide adequate structural support for the vertebral bodies, resulting in vertical disc herniation.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.331
Teacher spread0.304 · 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

Citations32
Published2015
Admission routes2
Has abstractyes

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Same venueAmerican Journal of Physical AnthropologySame topicMorphological variations and asymmetryFrench-language works237,207