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Record W4386237832 · doi:10.1123/ijatt.2022-0050

Assessment of Aerobic Fitness Following Anterior Cruciate Ligament Rupture and Reconstruction

2023· article· en· W4386237832 on OpenAlexaff
Dean M. Cordingley, Sheila McRae, Greg Stranges, Peter B. MacDonald

Bibliographic record

VenueInternational Journal of Athletic Therapy & Training · 2023
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsUniversity of ManitobaPan Am Clinic
Fundersnot available
KeywordsMedicineAnterior cruciate ligament reconstructionDeconditioningAerobic exerciseAnterior cruciate ligamentPhysical therapyRehabilitationPhysical fitnessSurgeryPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Following anterior cruciate ligament rupture, physical activity may be limited due to restrictions placed on the patient while awaiting reconstruction (anterior cruciate ligament reconstruction [ACLr]). The purpose of the study was to evaluate aerobic fitness in individuals undergoing ACLr at the time of medical clearance following injury, 6-month post-ACLr, and 12-month post-ACLr. Seventeen individuals participated in the research study to completion (females, n = 6, age = 23.3 ± 5.5 years; males, n = 11, age = 23.2 ± 4.7 years). There were no changes in aerobic fitness from baseline to 12-month postoperative, but due to the length of time between injury and baseline assessments, it is unknown if aerobic deconditioning occurred before the patient was assessed preoperatively.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.345
Teacher spread0.319 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2023
Admission routes1
Has abstractyes

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