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Record W2320690144 · doi:10.7719/jpair.v4i1.117

High Volume Low Density Culture of Milkfish (Chanos chanos Forsskal) in Floating Net Cages at North Bais Bay Manjuyod-side, Negros oriental

2010· article· en· W2320690144 on OpenAlexaff
Roger Ray S. Manzano, Peter L. Uy, Renato H. Ganancial

Bibliographic record

VenueJPAIR Multidisciplinary Research · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsMilkfishBayFisheryVolume (thermodynamics)BiologyGeographyFish <Actinopterygii>AquacultureArchaeologyPhysics

Abstract

fetched live from OpenAlex

The study was conducted at Resources Production Technology (REPROTECH), Incorporated in north Bais Bay (Manjuyod side), Negros Oriental. The purpose of the study is to demonstrate the feasibility and viability of milkfish (Chanos chanos forsskal) cultured in 180-m3 (6m x 6m x 5m) High Volume Low Density (HVLD) floating net cages and established a benchmark for cage farmers using a technology that offers a promising strategy that can have enormous impact on both socio-economic growth and food security. Results showed that bangus attained an average body weight (ABW) of 376.32 grams, after an average day of culture (DOC) of 163. It also showed an excellent survival rate of 111% and a very satisfactory feed conversion ratio (FCR) of 2.4. The average production per unit cage reached 2,480 kg or 13.78 kg/m3 of cage volume. The project realized a profit margin of Php. 34.94 per kilogram, indicating that even if the market price per kilogram is reduced by 10% the project is still gaining. Milkfish production in HVLD floating cages is economically viable for small and medium enterprise (SMI) fish farmers and promises a very attractive Return of Investment (ROI) estimated at 64.18% and a payback period of 0.4 year.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.294
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

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