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Record W2136013751 · doi:10.1109/iembs.2001.1020497

Differences between different posterior stabilization at atlanto-axial joint

2005· article· en· W2136013751 on OpenAlexaboutno aff
Chang Geng, Jia‐Hao Chang, C. H. Change, E.J. Lee, A.T. Hsu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFixation (population genetics)Internal fixationSpinal cordStiffnessSurgeryAtlanto-axial jointCervical spineOrthodonticsPhysical medicine and rehabilitationStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Summary form only given. Trauma and disorders are the major cause of spinal cord injuries at the C1-C level, which have resulted in complete or incomplete loss of sensory and motor functions. More and more accidents occur, which spend a lot of money in surgical treatment and rehabilitation. Conservative therapy or surgical treatment with internal fixation devices has been commonly used to stabilize the spine and enhance spine fusion for minimized compression in spinal cod leading to neurological deficits and other secondary injuries. The purpose of this research was to investigate the effect of various internal fixation devices for improving rotation stiffness of unstable atlanto-axial joint using a canine model. The results indicated that posterolateral plating provided the optimal stiffness across C1-2 in all the 6 tested directions than did the other 2 techniques although both the latter also had significantly increased stiffness compared to control group (P<0.05). Also, the results supported the use of each tested stabilization techniques for fixing the atlanto-axial instability. For preserving the optimal C1-2 motibility, procedures such as posterior wiring and/or Halifax interlaminar clamping rather than posterolateral plating and screwing should be considered first.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.002

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 head0.037
GPT teacher head0.294
Teacher spread0.258 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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