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Record W4241407394 · doi:10.25311/keskom.vol2.iss3.59

Karakteristik Wanita dengan Keluhan Masa Menopause di Wilayah Kerja Puskesmas Rejosari

2013· article· id· W4241407394 on OpenAlexaff
Liva Maita, Nurlisis Nurlisis, Risa Pitriani

Bibliographic record

VenueJurnal kesehatan komunitas (Journal of community health) · 2013
Typearticle
Languageid
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsGynecologyMenopauseMedicineInternal medicine

Abstract

fetched live from OpenAlex

Menopause merupakan fase terakhir dimana perdarahan haid seorang wanita berhenti sama sekali. Pada usia 50 tahun, perempuan memasuki masa menopause sehingga terjadi penurunan atau hilangnya hormon estrogen yang menyebabkan perempuan mengalami keluhan atau gangguan yang seringkali mengganggu aktivitas sehari-hari bahkan dapat menurunkan kualitas hidupnya. Penelitian ini dilakukan untuk mengetahui karakteristik wanita yang mengalami keluhan masa menopause di Puskesmas Rejosari. Penelitian ini bersifat kuantitatif analitik dengan desain cross sectional. Populasi dalam penelitian ini adalah seluruh wanita usia 45-59 tahun yang berkunjung di puskesmas Rejosari yang berjumlah 100 orang. Data yang digunakan merupakan data primer. Analisis yang digunakan analisis bivariat untuk mengetahui adanya hubungan karakteristik wanita dengan keluhan masa menopause. Hasil penelitian didapatkan umur wanita dan kondisi haid berhubungan dengan keluhan masa menopause sedangkan paritas, alat kontrasepsi, Indeks Masa Tubuh, pendidikan, pekerjaan, status pernikahan, dan pendapatan tidak berhubungan dengan keluhan masa menopause. Diharapkan kepada Puskesmas Rejosari untuk dapat memberikan penyuluhan tentang gizi yang baik menjelang menopause dan persiapan menghadapi menopause melalui pelaksanaan senam lansia secara rutin

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)0.008
metaresearch head score (Gemma)0.003
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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0010.014
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.331
Teacher spread0.293 · 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; both teacher heads agree on what is shown here.

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

Citations9
Published2013
Admission routes1
Has abstractyes

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