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Record W7004994032

PERFORMAN AYAM PETELUR UMUR 40 HARI -75 HARIYANG DIBERI EKSTRAK TEMULAWAK(Curcuma xanthorrizaRoxb) DENGANKONSENTRASI
\nYANG BERBEDA

2015· dissertation· id· W7004994032 on OpenAlexaff

Bibliographic record

VenueAnalisis Harga Pokok Produksi Rumah Pada (UIN Syarif Hidayatullah Jakarta) · 2015
Typedissertation
Languageid
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBenzyl benzoateBody weightHoneydew
DOInot available

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk melihat performan (konsumsi ransum, pertambahan bobot badan, konversi ransum) ayam petelur yang diberikan ekstrak temulawak dengan konsentrasi yang berbeda. Penelitian ini telah dilakukan di Kandang Percobaan Fakultas Pertanian dan Peternakan UIN Suska Riau. Penelitian ini berlangsung selama 35 hari, dimulai bulan September – Oktober 2013. Rancangan yang digunakan adalah rancangan acak lengkap (RAL) yang terdiri dari 4 perlakuan dan 7 ulangan. Perlakuan terdiri dari atas T0 ( 0 ml ekstrak temulawak), T1 (1 ml ekstrak temulawak), T2 ( 2 ml ekstrak temulawak), dan T3 (3 ml ekstrak temulawak). Ekstrak temulawak diberikan setiap hari dengan cara dicekok selama penelitian. Hasil penelitian menunjukkan bahwa pemberian ekstrak temulawak tidak berbeda nyata (P>0.05) terhadap konsumsi ransum rataannya yaitu 312.94 ± 11.88 g/ekor/minggu, rataan pertambahan bobot badan yaitu 254.10 ± 20.70 g/ekor/minggu dan konversi ransum yaitu 1.33 ± 0.24 . Pemberian ekstrak temulawak sampai dengan 3 ml tidak dapat meningkatkan konsumsi ransum, pertambahan bobot badan dan memperbaiki konversi ransum ayam petelur. Perlu dilakukan penelitian yang sama terhadap performan ayam petelur dengan penambahan level ekstrak temulawak dengan konstentrasi yang berbeda.
\nKata kunci : Performan ayam petelur, ekstrak temulawak, konsentrasi yang berbeda.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0010.002

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 head0.017
GPT teacher head0.268
Teacher spread0.250 · 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 designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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