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Record W4388187727 · doi:10.47767/nekton.v3i2.497

Teknis Pengelolaan Pembenihan Ikan Mas Mantap Cyprinus carpio untuk Mendapatkan Benih Kualitas Unggul

2023· article· en· W4388187727 on OpenAlexaff
Andri Iskandar, Odang Carman, Astri Ayuningtias, Tatang Juanda, Rahmat Hidayat

Bibliographic record

VenueNekton · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsCyprinusCarpBroodstockBiologyHatchingFecundityFisheryCommon carpHuman fertilizationFish farmingFish <Actinopterygii>Animal scienceToxicologyAquacultureAgronomyPopulation

Abstract

fetched live from OpenAlex

The development of mirror carp (Cyprinus carpio) farming in Indonesia has progressed very rapidly, as can be seen by the increasing number of varieties of mirror carp produced from various regions with their respective specifications and advantages. Along with the need for carp that are more resistant to environmental changes and disease attacks, the development of the Majalaya carp variety subsequently produces Mantap carp fish that are disease-resistant, and growth in the growth segment is faster. The aim of this study was to disseminate technical information on Mantap fish carp culture to the public so that it can be used as a reference source for the community, especially for cultivators who are interested in developing this fish. In this study, primary and secondary data were collected. Based on the results of a fecundity study, one female broodstock produced 104.496 kg broodstock-1, the average percentage of egg fertilization (FR) was 89,64%, the average hatching rate (HR) was 61,37%, and the average survival rate (SR) until the size of the seed size 2-3 cm reaches 60%.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.222
Teacher spread0.192 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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