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Record W2328146029 · doi:10.3928/01477447-20100722-27

The Proximal Modular Neck in THA: A Bridge Too Far: Opposes

2010· letter· en· W2328146029 on OpenAlexaff
Hugh U. Cameron

Bibliographic record

VenueOrthopedics · 2010
Typeletter
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsThe Scarborough Hospital
Fundersnot available
KeywordsMedicineSurgeryOrthodontics

Abstract

fetched live from OpenAlex

Neck/cup impingement is a serious issue, especially with hard/hard bearings. It can produce noise, locking mechanism failure, and an increase in wear debris and dislocation. The double taper neck used by the author has cogs on the neck/stem taper junction for additional rotational stability. One hundred forty-six procedures were performed using the thin mantle cement technique. Mean follow-up was 5 years (range, 3-8 years). A 32-mm neck was used in 73.8% of cases and a 35-mm neck in 26.2%, because most of the patients were elderly women. The neck was anteverted in 1.4%, neutral in 26.4%, and retroverted in the rest (mild in 34.2%, moderate in 14.3%, and maximum in 13.4%). There were no dislocations and no loosenings. Problems were encountered with the neck/stem taper in 3 cases. The stem was therefore taken off the market. The taper was lengthened and the strength doubled. Since its reintroduction 3 years ago, a further 187 cemented stem procedures have been performed with no failures and no dislocations. Of interest in this series, no necks were anteverted, 23.5% were in neutral, 35.8% were in mild retroversion, 31.1% were in moderate retroversion, and 9.6% were in maximal retroversion. Most necks were placed in retroversion to avoid impingement. This suggests that if a nonmodular neck had been used, some degree of impingement would have occurred in 70% of cases.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.262
Teacher spread0.241 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2010
Admission routes1
Has abstractyes

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