MétaCan
Menu
Back to cohort
Record W4407792372 · doi:10.2106/jbjs.cc.24.00536

Guided Growth for Posterior Tibial Slope Correction Followed by ACL Reconstruction in an Adolescent Male

2025· article· en· W4407792372 on OpenAlexaff
Benjamin Blackman, Manpreet Singh Sidhu, Ajay Shah, Jennah Mann, Paul Marks, David Wasserstein

Bibliographic record

VenueJBJS Case Connector · 2025
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsOrthodonticsMedicine

Abstract

fetched live from OpenAlex

CASE: A 13-year-old adolescent boy presented with chronic anterior cruciate ligament (ACL) insufficiency and prior medial meniscectomy. Radiographic evaluation revealed a posterior tibial slope (PTS) of 20°, putting him at high risk of reinjury following ACL reconstruction (ACLR). Guided growth using anteriorly placed eight plates was used for 9 months, which reduced his PTS to 6°. Two months following plate removal, the patient underwent ACLR with lateral extra-articular tenodesis. CONCLUSION: This previously proposed but never reported approach suggests that guided growth is a viable option to correct excessive PTS before ACLR in skeletally immature patients.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.307
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 designCase report
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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJBJS Case ConnectorSame topicKnee injuries and reconstruction techniquesFrench-language works237,207