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Record W2613389238

Optimizing Spinal Implants through Modeling

2016· other· en· W2613389238 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEspace ÉTS (ETS) · 2016
Typeother
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsnot available
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsRodStiffnessFlexural rigidityScoliosisSpinal fusionMaterials scienceFusionTransverse planeSpinal cord injuryMedicineSpinal cordSurgeryComposite materialAnatomy
DOInot available

Abstract

fetched live from OpenAlex

Fusion surgery is frequently used for treating scoliosis, fractures or spinal cord injury. Following fusion surgery, adjacent segments complications occur in up to 40% of the patients. Because of the high stiffness of the posterior instrumentations conventionally used, a stress concentration is created at the extremities of the implants, leading to adjacent segment complications. An innovative concept of shape memory alloys rods with variable flexural stiffness is proposed to lower the stress observed on the adjacent segments. Local Joule effect annealing was used to produce biocompatible rods with decreased proximal stiffness. The variable rods combined with transverse process hooks as upper anchors decrease the stress concentration at the adjacent segment and the pullout forces on the proximal anchors.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.194
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.011

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 head0.300
Teacher spread0.267 · 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