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Record W2108593483 · doi:10.1186/s13018-014-0058-7

An intraoperative device to restore femoral offset in total hip arthroplasty

2014· article· en· W2108593483 on OpenAlexaff
Enxing Xue, Zhen Su, Chengwang Chen, Paul Wong, Hong Wen, Yufan Zhang

Bibliographic record

VenueJournal of Orthopaedic Surgery and Research · 2014
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineOrthopedic surgeryRadiographyLeverTotal hip arthroplastySurgeryFemoral headArthroplastyNuclear medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Leg length discrepancy (LLD) after total hip arthroplasty (THA) can lead to unsatisfactory outcome. Our objective was to design and evaluate a simple and reliable intraoperative device (Length-offset Lever) to minimize leg length discrepancy. METHODS: This device was used in 51 patients undergoing primary total hip replacements. The leg length discrepancy was measured pre- and postoperatively based on plain radiographs. RESULTS: Preoperative radiographic leg length discrepancy averaged 13.5 ± 6.2 mm. Leg length discrepancy showed significant improvement, with a postoperative average of 4.1 ± 2.3 mm (p < 0.0001). There were no complications associated with this device. CONCLUSIONS: The 'Length-offset Lever' is a useful intraoperative tool to restore anatomic femoral offset and height of femoral head.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.363
Teacher spread0.302 · 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 designBench or experimental
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

Citations6
Published2014
Admission routes1
Has abstractyes

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