MétaCan
Menu
← Back to cohort
Record W2991382347 · doi:10.36959/453/516

Arthroscopic Anterior Cruciate Ligament (ACL) Reconstruction Using Hamstring Tendon at the Order of Malta's Hospital Center in Dakar

2017· article· en· W2991382347 on OpenAlexaboutno aff
CVA Kinkpe

Bibliographic record

VenueJournal of Orthopedic Surgery and Techniques · 2017
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsLachman testAnterior cruciate ligamentPivot-shift testMedicineTest (biology)HamstringOrthodonticsAnterior cruciate ligament reconstructionPhysical therapyPhysical medicine and rehabilitationSurgeryGeology

Abstract

fetched live from OpenAlex

The diagnosis is based mainly on clinical examination (Lachman test, anterior drawer test, and pivot shift test). These tests have very different sensitivities and specificities depending on the experience of the examiner, the patient's body type, and the delay between the accident and examination . Recently, a new arthrometer, the GNRB (Genourob, Laval, France) was developed to alleviate the difficulties of using the KT-1000 with partially trained examiners Thearthrometer is powered and incorporates pressure and movement sensors facilitating more accurate measurements.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.294
Teacher spread0.276 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Orthopedic Surgery and Techniques→Same topicKnee injuries and reconstruction techniques→French-language works237,207→