MétaCan
Menu
Back to cohort
Record W4378619025 · doi:10.30649/sbj.v2i3.92

HUBUNGAN ANTARA INDEKS MASA TUBUH DENGAN TINGGI SKOR WESTERN ONTARIO AND MCMASTER UNIVERSITY OSTEOARTHRITIS INDEX PADA PASIEN OSTEOARTHRITIS LUTUT DI RSPAL DR. RAMELAN SURABAYA

2023· article· id· W4378619025 on OpenAlexaffabout
Muhammad Habib Hanif Hanif

Bibliographic record

VenueSurabaya Biomedical Journal · 2023
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicMedicinal Plant Research
Canadian institutionsOsteoporosis CanadaJuravinski Cancer Centre
Fundersnot available
KeywordsGynecologyMedicineWOMACOsteoarthritis

Abstract

fetched live from OpenAlex

IMT (Indeks Masa Tubuh) adalah suatu indeks statistik yang menggunakan berat dan tinggi badan seseorang untuk memberikan estimasi pengukuran lemak tubuh seseorang. Nilai IMT ≥ 30 menunjukkan seseorang tersebut mengalami obesitas. Obesitas merupakan salah satu faktor risiko osteoarthritis lutut, dimana untuk menilai tingkat keparahan osteoarthritis lutut salah satunya menggunakan penilaian tinggi skor WOMAC (Western Ontario and McMaster University Osteoarthritis Index). WOMAC adalah pengukuran yang digunakan untuk menilai pasien dengan osteoarthritis pada ekstremitas bawah. Penelitian ini dilakukan untuk mengetahui hubungan antara indeks masa tubuh dengan tinggi skor WOMAC pada pasien osteoarthritis lutut di RSPAL Dr. Ramelan Surabaya. Penelitian ini termasuk kedalam jenis penelitian analitik observasional dengan desain penelitian menggunakan cross sectional study. Data yang diperoleh dari pengisian kuesioner WOMAC dilakukan pada 29 pasien osteoarthritis lutut di RSPAL Dr. Ramelan Surabaya. Pemilihan sampel menggunakan total sampling. Berdasarkan hasil uji korelasi Spearman didapatkan hasil signifikansi antara indeks masa tubuh dengan tinggi skor WOMAC sebesar (p=0,182). Artinya variabel indeks masa tubuh tidak berhubungan dengan tinggi skor WOMAC. Tidak ada hubungan antara indeks masa tubuh dengan tinggi skor WOMAC pada pasien osteoarthritis lutut di RSPAL Dr. Ramelan Surabaya.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.236
Teacher spread0.213 · 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.

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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueSurabaya Biomedical JournalSame topicMedicinal Plant ResearchFrench-language works237,207