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Pre and post-operative rehabilitation of anterior cruciate ligament reconstruction in young athletes

2017· article· en· W2608520200 on OpenAlexafffund
Qais Gasibat, Alhadi M. Jahan

Bibliographic record

VenueInternational Journal of Orthopaedics Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsUniversity of Ottawa
FundersUniversiti Sultan Zainal AbidinUniversity of Ottawa
KeywordsMedicineAthletesRehabilitationAnterior cruciate ligament reconstructionAnterior cruciate ligamentReturn to sportPhysical therapyOrthodonticsSurgery

Abstract

fetched live from OpenAlex

Background: Anterior Cruciate Ligament (ACL) injury and reconstruction surgeries are common among young athletes, who are frequently involved in sports activities. Research suggests that ACL injuries among sportsmen have the longest disability time and the most expensive to treat. The pre and post-operative rehabilitation exercise of ACL ruptures continues to be controversial. Objectives: The aim of this review is to systematically review the current evidence of the exercise therapy for pre and post-operative stages, and to identify uncovered issues for future investigations. Methods: Three databases: Medline, Pedro, and Cinahl were searched for all published literature from 1975 to 2017 using key words such as,

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)0.002
metaresearch head score (Gemma)0.010
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.334
Teacher spread0.323 · 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

Citations14
Published2017
Admission routes2
Has abstractyes

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