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Penentuan Aktivitas Antioksidan dari Tiga Jenis Simplisia Jahe (Gajah, Emprit, Merah) untuk Pengobatan Tradisional Chinese Medicine (TCM)

2024· article· id· W4399516882 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMajalah Farmasetika · 2024
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicMedicinal Plant Research
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTraditional medicineMedicine

Abstract

fetched live from OpenAlex

Jahe merupakan tanaman yang banyak dibudidayakan di Indonesia. Rimpang jahe diketahui mempunyai banyak khasiatnya terhadap kesehatan. Jahe sering dijumpai dalam racikan pengobatan Traditional Chinese Medicine (TCM). Hal ini ada kaitannya dengan kandungan antioksidan pada jahe. Tujuan Penelitian ini bertujuan untuk menentukan aktivitas antioksidan pada simplisia tiga jenis simplisia jahe (gajah, emprit, merah). Metode Tiga jahe diberikan perlakuan yaitu sortasi basah dan kering, pembuatan simplisia, karakterisasi simplisia, uji aktivitas antioksidan menggunakan metode 2,2-Diphenyl-1-picrylhydrazyl (DPPH). Hasil rendemen simplisia tiga jahe (gajah 19,00%, emprit 15,26%, merah 12,61%), pengujian kadar air simplisia dari tiga jahe (gajah 7,315 %, emprit 7,439%, merah 8,576 %) selanjutnya pada penentuan uji aktivitas antioksidan jahe gajah 77,03%, jahe emprit 61,91%, jahe merah 67,94%. aktivitas Aktivitas antioksidan dari ketiga jahe dengan metode DPPH menunjukkan nilai inhibitory concentration (IC50 ) mempunyai kategori kuat yaitu ada diantara 50-100 µg/ml.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0290.003

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 head0.029
GPT teacher head0.309
Teacher spread0.280 · 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