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Record W2991329509 · doi:10.2217/3dp-2019-0012

Investigation of Future 3D Printed Brace Design Parameters: Evaluation of Mechanical Properties and Prototype Outcomes

2019· article· en· W2991329509 on OpenAlexaff
Kuang Yee Ng, Kajsa Duke, Edmond Lou

Bibliographic record

VenueJournal of 3D Printing in Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBraceFlexibility (engineering)Materials scienceIdiopathic scoliosisStructural engineeringScoliosisMedicineEngineeringSurgeryMathematics

Abstract

fetched live from OpenAlex

Aim: Spinal brace wear time affects treatment effectiveness of adolescent idiopathic scoliosis but remains challenging with the brace’s bulkiness. This study aims to determine the appropriate material and thickness to improve wear comfort. Materials & methods: Thirty-one specimens were tested with 13 ULTEM1010 and 13 Nylon12 potential materials and 5 standard polypropylene material in 2.5, 3.25 and 4 mm thicknesses to evaluate mechanical properties. Donning tests of ULTEM1010 and Nylon12 printed braces were conducted. Results: Nylon12 with 2.5–3.25 mm thickness had higher flexibility and the closest mechanical characteristics as 4-mm thick polypropylene. ULTEM1010 brace fractured after 615-times and Nylon12 brace handled 2920-times of opening and closing. Conclusion: Nylon12, 2.5–3.25 mm are appropriate design parameters. Further clinical study can validate long term brace effectiveness.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.064
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.150
GPT teacher head0.345
Teacher spread0.195 · 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 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

Citations13
Published2019
Admission routes1
Has abstractyes

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