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Record W4409713999 · doi:10.35472/maximus.v2i2.1757

Laboratory Scale Brachionus plicatilis Culture Technique with Natural Feeds Nannochloropsis oculata and Tetraselmis chuii in Marine Aquaculture Center Lampung, Teluk Pandan, Pesawaran

2024· article· en· W4409713999 on OpenAlexaff
Gres Maretta

Bibliographic record

VenueMaximus · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsEmera (Canada)
Fundersnot available
KeywordsTetraselmisBrachionusAquacultureBiologyFood scienceAlgaeBotanyFisheryFish <Actinopterygii>Larva

Abstract

fetched live from OpenAlex

A very influential factor in marine fish production is the provision of efficient and appropriate feed and feed management for marine fish larvae. Natural feed has content that can meet the nutritional needs of marine fish larvae. One of the natural feeds that can be utilized in marine fish farming is rotifer (Brachionus plicatilis). This study aims to determine the laboratory scale culture technique of Brachionus plicatilis, determine the growth rate of Brachionus plicatilis with different phytoplankton feeding, determine the optimal phytoplankton density for Brachionus plicatilis. Data collection techniques in this study used 2 kinds of data, namely primary data and secondary data. Primary data comes from observation, interviews, and active participation. While secondary data comes from literature studies, namely books, journals, annual reports, theses, and so on. Laboratory-scale Brachionus plicatilis culture starts from sterilization of tools and materials, planting Brachionus plicatilis seedlings, feeding, and calculating the population of Brachionus plicatilis. Brachionus plicatilis fed with Nannochloropsis oculata at a density of 100,000 cells/ml entered the exponential phase on day 4 with a total number of individuals of 72 ind/ml, while Brachionus plicatilis fed with Tetraselmis chuii at a density of 3000 cells/ml entered the exponential phase on day 5 with a total number of individuals of 100 ind/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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.354

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)0.0000.000

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 head0.005
GPT teacher head0.197
Teacher spread0.191 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes1
Has abstractyes

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