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Record W4411555852 · doi:10.1115/1.4069004

A New Slant on Shear Loading: Uncovering Its Effect on the Intervertebral Disc

2025· article· en· W4411555852 on OpenAlexafffund
Eliana Seider, Sabrina I. Sinopoli, Diane E. Gregory

Bibliographic record

VenueJournal of Biomechanical Engineering · 2025
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShear (geology)Intervertebral discGeologyMaterials scienceOrthodonticsComposite materialMedicineAnatomy

Abstract

fetched live from OpenAlex

Prolonged anterior shear loading may contribute to disc degeneration by damaging the annulus fibrosus. To address this, annular mechanical properties were quantified following static shear loading using a porcine model. Twelve porcine cervical motion segments were dissected, with posterior bony elements removed to isolate shear to the intervertebral disc. Specimens were randomized into two conditions: (1) shear-loaded (100 N static anterior shear applied to C3/C4, n = 6) or (2) control (0 N, n = 6). Shear force was applied via a pin through C4, secured to a testing system to prevent rotation, while C3 was clamped such that anterior shear of C3 with respect to C4 resulted. Following 1 h of loading, two anterior annulus samples were extracted per specimen. The first sample underwent circumferential tensile testing, while the other was prepared for a peel test to assess interlamellar adhesion. Tensile properties in the circumferential direction remained unchanged after shear loading. However, interlamellar adhesive stiffness decreased by 52% (p = 0.02), and adhesive strength dropped by 46% (p = 0.02) in shear-loaded specimens compared to controls. Shear loading weakened the interlamellar matrix, reducing resistance to delamination and compromising disc integrity. These findings suggest that prolonged shear loading may contribute to early-stage disc damage.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.434

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 integrity0.0000.001
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 head0.014
GPT teacher head0.275
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2025
Admission routes2
Has abstractyes

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