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Record W4213296978 · doi:10.55313/ojs.v7i1.54

Penerapan Range Of Motion (ROM) Pada Penderita Stroke: Studi Kasus

2020· article· id· W4213296978 on OpenAlexaff
Raudhotun Nisak, Aditya Dwi Prabowo

Bibliographic record

Venuee-Journal Cakra Medika · 2020
Typearticle
Languageid
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Latar belakang: Stroke adalah cedera otak traumatis yang mendadak, progresif, dan cepat yang disebabkan oleh gangguan nontraumatik pada aliran darah ke otak yang dapat menimbulkan berbagai gejala pada penderitanya. Penderita stroke dapat diberikan proses rehabilitasi berupa salah satu latihan gerak atau sering latihan Range Of Motion (ROM) untuk mencegah kecacatan lebih lanjut. Tujuan penelitian ini adalah untuk mengetahui gambaran penerapan ROM pada penderita stroke. Metode: Desain penelitian yang digunakan adalah studi kasus dengan menggunakan metode deskriptif. Subjek penelitian adalah penderita stroke yang ada di Wilayah Kerja Puskesmas Karanganyar selama 10 hari. Hasil: Hasil penelitian menunjukkan bahwa terdapat peningkatan kekuatan otot sebelum dan setelah penerapan ROM. Kesimpulan: ROM merupakan salah satu bentuk tindakan rehabilitatif yang dapat digunakan meningkatkan kekuatan otot pada penderita stroke. Keluarga diharapkan dapat terlibat dalam tindakan ROM khsusnya pada ROM pasif.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.157
GPT teacher head0.441
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2020
Admission routes1
Has abstractyes

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