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Record W2111981845 · doi:10.1073/pnas.0905235106

Feeding aquaculture in an era of finite resources

2009· review· en· W2111981845 on OpenAlexaff
Rosamond L. Naylor, Ronald W. Hardy, Dominique Bureau, Alice P. Y. Chiu, Matthew Elliott, Anthony P. Farrell, Ian Forster, Delbert M. Gatlin, Rebecca J. Goldburg, Katheline Hua, Peter D. Nichols

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2009
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsVancouver AquariumUniversity of Guelph
FundersDavid and Lucile Packard Foundation
KeywordsAquacultureFish mealFisheryFish <Actinopterygii>Fish oilIncentiveBusinessForageNatural resource economicsBiologyEconomicsEcology

Abstract

fetched live from OpenAlex

Aquaculture's pressure on forage fisheries remains hotly contested. This article reviews trends in fishmeal and fish oil use in industrial aquafeeds, showing reduced inclusion rates but greater total use associated with increased aquaculture production and demand for fish high in long-chain omega-3 oils. The ratio of wild fisheries inputs to farmed fish output has fallen to 0.63 for the aquaculture sector as a whole but remains as high as 5.0 for Atlantic salmon. Various plant- and animal-based alternatives are now used or available for industrial aquafeeds, depending on relative prices and consumer acceptance, and the outlook for single-cell organisms to replace fish oil is promising. With appropriate economic and regulatory incentives, the transition toward alternative feedstuffs could accelerate, paving the way for a consensus that aquaculture is aiding the ocean, not depleting it.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.080
GPT teacher head0.327
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1,500
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicAquaculture Nutrition and GrowthFrench-language works237,207