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Record W3094298745 · doi:10.1519/ssc.0000000000000605

Optimizing Exercise Selection for the Asymmetric Athlete After Anterior Cruciate Ligament Reconstruction

2020· article· en· W3094298745 on OpenAlexaff
Dan Ogborn

Bibliographic record

VenueStrength and conditioning journal · 2020
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsUniversity of ManitobaPan Am Clinic
Fundersnot available
KeywordsSquatPhysical medicine and rehabilitationAnterior cruciate ligamentAnterior cruciate ligament reconstructionReturn to sportMedicinePlyometricsPhysical therapyAthletesAnatomyJump

Abstract

fetched live from OpenAlex

ABSTRACT Persistent deficits in quadriceps strength occur after anterior cruciate ligament (ACL) reconstruction and should be addressed to facilitate safe return to sport. Asymmetric movement patterns that shield the affected knee by shifting demands to the unaffected lower extremity, or other joints within the affected limb, may limit the ability of common strength training exercises to effectively mitigate quadriceps weakness. A multifaceted approach focusing on the early restoration of symmetrical loading during the squat, programming isolated knee extensions, and varying exercise selection to include split-stance positions, such as the split-squat and lunge, may result in the successful restoration of quadriceps strength after ACL reconstruction.

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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
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)0.0020.001

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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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
GenreMethods

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

Citations2
Published2020
Admission routes1
Has abstractyes

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