MétaCan
Menu
Back to cohort
Record W2125392852 · doi:10.1155/2013/646598

Infraspinatus/Teres Minor Transfer Biceps In Situ Tenodesis Procedure: Initial Results of a Technique for Massive Cuff Tears

2013· article· en· W2125392852 on OpenAlexaff
Matthew Fletcher

Bibliographic record

VenueISRN Orthopedics · 2013
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsDawson College
Fundersnot available
KeywordsRotator cuffTearsBicepsTendon transferMedicineSurgeryTendonCuff

Abstract

fetched live from OpenAlex

Massive rotator cuff tears may not be primarily repairable with salvage options not necessarily providing acceptable results. Extrinsic tendon transfer is a significant undertaking with prolonged rehabilitation and variable outcome. A novel technique for the reconstruction of massive tears, not amenable to primary repair, by performing a transfer of the intrinsic posterior rotator cuff onto an intact, tenodesed long head of biceps tendon acting as a scaffold for the intrinsic transfer is described. The clinical results at short to medium term in 17 initial patients are presented. Encouraging results from this study suggest that this is a viable option for the management of massive rotator cuff tears with an intact posterior cuff with results equal or superior to other reconstructive techniques.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.026
GPT teacher head0.319
Teacher spread0.293 · 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 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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueISRN OrthopedicsSame topicShoulder Injury and TreatmentFrench-language works237,207