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Record W2113503063 · doi:10.5539/mas.v9n1p184

The Influence of Substrate to Larval Settlement of the Tropical Abalone (Haliotis asinina)

2014· article· en· W2113503063 on OpenAlexvenueno aff
St Hadijah, Zainuddin E. Viky

Bibliographic record

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbaloneLarvaSubstrate (aquarium)FisheryBiologyAquacultureEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Larval settlement stage of abalone (Haliotis asinine) depends on availability of feed and substrate compatibility. Existing feed size and feed type diversity in substrate will affect larval settlement stage, feeding habit and survival rate of abalone larvae. This study aims to find out the most suitable substrate for larval settlement of the tropical abalone. It is conducted in February-April, 2013 at Brackish Water Aquaculture Center, Takalar Regency, South Sulawesi. Applied experimental design is Completely Randomized Design. There are 3 types of test substrate: coral, cement and plastic with 3 replications for each substrate. This study shows that statistically, substrate differences do not affect to larval settlement stage. The highest stage of larval settlement is to coral substrate by 3.3%, followed by cement and plastic by 2.2% and 0.2% respectively. The highest average stage of living larva on coral and cement substrate are 15.3%, while on plastic substrate is 8.7%.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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