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Record W4312480895 · doi:10.20884/1.bioe.2022.4.2.4685

[no title]

2022· article· W4312480895 on OpenAlexaff
Amanda Rohmatun Hasanah, Aris Mumpuni, Nuraeni Ekowati

Bibliographic record

VenueBioEksakta Jurnal Ilmiah Biologi Unsoed · 2022
Typearticle
Language
FieldHealth Professions
TopicAdolescent Health and Behaviors
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysicsBiologyTraditional medicineMedicine

Abstract

fetched live from OpenAlex

Jamur koprofil merupakan suatu kelompok jamur yang tumbuh pada kotoran hewan herbivora. Beberapa jenis jamur koprofil merupakan jamur edibel yang dapat dikembangkan sebagai penyedia protein, serta beberapa di antaranya juga merupakan jamur beracun khususnya mengandung senyawa psikotropika yang dapat diambil manfaat positifnya sebagai bahan pembuatan obat penenang. Penelitian mengenai deteksi senyawa psikotropika pada jamur kotoran hewan ternak masih belum banyak dilakukan. Kondisi lingkungan di wilayah Kecamatan Karanglewas didapatkan tumbuhnya jamur koprofil di wilayah tersebut. Jamur koprofil mempunyai potensi yang dapat dimanfaatkan ataupun disalahgunakan oleh masyarakat, oleh karena itu penelitian ini perlu dilakukan untuk mempelajari keberadaan jamur-jamur koprofil dan senyawa psikotropika yang terkandung dalam jamur koprofil. Penelitian ini bertujuan untuk mengidentifikasi jamur koprofil yang tumbuh pada kotoran sapi di wilayah Kecamatan Karanglewas Kabupaten Banyumas serta mendeteksi keberadaan senyawa psikotropika pada tubuh buah maupun miselium jamur koprofil yang diperoleh. Hasil penelitian diperoleh tujuh genera jamur koprofil yang didapatkan dari kandang sapi di Kecamatan Karanglewas Kabupaten Banyumas yaitu Coprinopsis, Mycena, Panaeolus, Inocybe, Ascobolus, Psilocybe, dan Coprinus. Senyawa psikotropika baik pada tubuh buah maupun miselium jamur koprofil terdeteksi pada empat genera yaitu Coprinopsis, Panaeolus, Inocybe, dan Psilocybe.

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)0.015
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.002
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0020.006
Science and technology studies0.0420.002
Scholarly communication0.0000.001
Open science0.0070.010
Research integrity0.0030.025
Insufficient payload (model declined to judge)0.0100.001

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 head0.140
GPT teacher head0.415
Teacher spread0.276 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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