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Record W569053855 · doi:10.1520/stp11146s

Vertebral Bone Density—A Critical Element in the Performance of Spinal Implants

2003· book-chapter· en· W569053855 on OpenAlexaff
JS Tan, B K Kwon, Dinesh Samarasekera, MF Dvorak, CG Fisher, TR Oxland

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsVancouver Spine Surgery Institute
Fundersnot available
KeywordsMedicineVertebral bodyOrthodonticsAnatomy

Abstract

fetched live from OpenAlex

The effectiveness of spinal implants in fixation is dependent upon the bone-implant interface, and thus on vertebral bone density. Current ASTM assessment methods use synthetic elements as vertebral surrogates and therefore, by definition, do not address important in vivo performance and failure characteristics. The purpose of this study is to contrast the mechanical behaviour of pedicle screws in cadaveric vertebrae versus synthetic surrogates. Short-term physiologic axial compression and bending moment were cyclically applied to pedicle screws inserted in lumbar vertebrae and UHMWPE. Kinematics of the pedicle screws in bone and in UHMWPE were significantly different in terms of the range of motion and pivoting and bending points on the screws. For the vertebral fixation, there was a trend towards a more rigid screw-bone interface with increasing bone mineral density. Devices tested using ASTM and ISO test standards may give clinicians and regulatory bodies a false sense of security with respect to implant performance due to their limited scope.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.033
GPT teacher head0.308
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2003
Admission routes1
Has abstractyes

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