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Record W4310114943 · doi:10.16899/jcm.1123734

Comparison of the Effects of Different Molecular Weight Hyaluronic Acid Application in Knee Osteoarthritis

2022· article· en· W4310114943 on OpenAlexaboutno aff
Ali ÇOŞTU

Bibliographic record

VenueJournal of Contemporary Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACMedicineOsteoarthritisVisual analogue scaleHyaluronic acidPhysical therapySurgery

Abstract

fetched live from OpenAlex

Objective: The objective of this study was to evaluate the effect of different molecular weight (MW) hyaluronic acid (HA) application on pain and functional parameters in knee osteoarthritis (OA). Methods: This study was designed as retrospectively. Hospital records of the patients who received intraarticular HA injection therapy in our center were screened. The patients were divided into 3 categories according to the MW of the preparates as the follows; Group 1: 0,6-1,2 Milion Da of MW (N=26); Group 2: 1,1- 2,2 Million Da of MW (N=25); and Group 3: 1,7-2,1 Million Da of MW (N=25). All patients were assessed using Visual Analogue Scale (VAS) and Western Ontario and McMaster Universities Arthritis Index (WOMAC) before the treatment and one month after the injection. Results: A total of 76 patients (61 females, 15 males) with a mean age of 62,1 years (minimum-maximum: 50-70 years) were included. VAS and WOMAC scores did improve significantly in all groups (all for p

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.270
Teacher spread0.259 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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