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Record W3133440485 · doi:10.1016/j.smhs.2021.02.005

High intensity resistance training as intervention method to knee osteoarthritis

2021· article· en· W3133440485 on OpenAlexaboutno aff
Andrea Malorgio, Marta Malorgio, Matteo Benedetti, S. Casarosa, Roberto Cannataro

Bibliographic record

VenueSports Medicine and Health Science · 2021
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACPhysical therapyOsteoarthritisMedicineResistance trainingStrength trainingIntensity (physics)IsotonicPhysical medicine and rehabilitationOne-repetition maximumAlternative medicine

Abstract

fetched live from OpenAlex

High intensity resistance training (HI-RT) is a treatment option for Knee Osteoarthritis (KOA). Isotonic machines (leg press, leg extension) are utilized for standardization and reproducibility reasons, but the load used during the protocol is often low, considering that elder people usually have low strength levels, training so with high intensities calculated on low loads. The physiological response of an elder woman trained with high loads on a free weight exercise, the regular barbell deadlift, with a 1 Repetition Maximum (1RM) of 100 kg, can be appreciated in this report, so that for the first time we can see the effect of a one year of high intensity resistance training program on a powerlifting exercise on a 72 year-old woman with KOA. A Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire was administered before starting the training program (T0) and after 1 year of training, as long as a control RX, to evaluate the effect of HI-RT on joint functionality and quality of life.

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)0.002
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 score0.979
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.052
GPT teacher head0.377
Teacher spread0.325 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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