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Record W3186650655 · doi:10.1002/naaq.10211

Economic Effect of Hybrid Catfish (Channel Catfish ♀ × Blue Catfish ♂) Growth Variability on Traditional and Intensive Production Systems

2021· article· en· W3186650655 on OpenAlexaff
Kamal Gosh, David Drescher, Dalton Robinson, William S. Bugg, Nagaraj Chatakondi, Ganesh Kumar, Carl Jeffers, Rex A. Dunham

Bibliographic record

VenueNorth American Journal of Aquaculture · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCatfishIctalurusStockingBiologyFisheryHectareProduction (economics)Animal scienceFish <Actinopterygii>Agricultural scienceEconomicsEcologyAgricultureMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Using hybrid catfish (Channel Catfish Ictalurus punctatus ♀ × Blue Catfish I. furcatus ♂) is one path toward intensification that can lower production costs and increase net returns. However, hybrid catfish have experienced growth variability resulting in undersized and oversized fish. Analyzing the economic effect of this issue is critical, as fish processors often require a specific size range of fish from the producers. Comparative economic analyses were performed using enterprise budgets and sensitivity analyses on hybrid catfish production data obtained from single-batch (SB), multiple-batch (MB), and split-pond (SP) systems. Results indicated that the SP system had the highest net returns (US$8,164/ha) resulting from greater availability of premium-sized fish (0.45–1.81 kg; sales price = $2.46/kg), followed by SB and MB systems, respectively. Lower prices received for undersized (&amp;lt;0.45 kg; sales price = $2.34/kg) and oversized (&amp;gt;1.81 kg; sales price = $2.08/kg) fish resulted in revenue losses of $287, $594, and $611 per hectare in SB, MB, and SP systems, respectively. An inverse relationship between the dockage rate and net returns was observed. Economic analyses also showed that the net returns were greater when large-sized fingerlings (~20 cm) were stocked relative to medium-sized fingerlings (≤18 cm) in the SP and SB systems, while the opposite was true for the MB system. Stocking of graded hybrids in SB, MB, and SP production could provide higher net returns from these systems.

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)0.001
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 score0.225
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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