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Record W2379293043

The Experimental Study and Clinical Application of Effect of the Vertical Stress on the Pelvic Ring

2002· article· en· W2379293043 on OpenAlexaff
Lei Guo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsSacrumAcetabulumPelvisSacroiliac jointJoint (building)GeologyDome (geology)AnatomyArchMedicineStructural engineeringGeomorphologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Objective: Our aim was to investigate the biomechanic characteristic of the pelvic ring under the vertical stress by the 3-dimensional photoelastics. Methods: Eight photoelastic pelvic models (16 hip joints) were made with light-sensatory material with hypersensitivity E-51 epoxy resin. The various vertical loading was put on the pelvic models, while the froze stress was performed. We analyzed the distribution and change of pelvic model stresses. Results: With the standing condition of double legs and vertical stresses, the streaks on the pictures of identical color-string were centralized on the sacroiliac joint and the acetabulum. The vertical stresses on the pelvis were transmitted through the sacroilic joint, the arch line of ilium, the dome of acetabulum, and the sacrum. When the vertical stresses on the pelvis increased, the stresses increased significantly on the sacroilic joint, arch line of ilium, the dome of acetabulum, and the sacrum ( P 0.05 ), but did not change obviously on the pubic superioris ( P 0.05). Conclusion: With the vertical stresses, the distribution of pelvic stresses is complicated. With the vertical stresses, the fractures occurred easily on the sacroilic joint, arch line of ilium, the dome of acetabulum, and the sacrum. The pubic superioris can transmit the vertical stresses. It is necessary to treat vertically unstable pelvic fractures with replacement and internal fixed the injured pelvic ring.

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)0.000
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 score0.304
Threshold uncertainty score0.099

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 science0.0000.000
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 head0.022
GPT teacher head0.339
Teacher spread0.317 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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