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Record W3080870840 · doi:10.1002/nafm.10512

Biology and Ecology of Grass Carp in China: A Review and Synthesis

2020· review· en· W3080870840 on OpenAlexaff
Yingming Zhao, Liang Zhang, Chunfang Wang, Congxin Xie

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2020
Typereview
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of WindsorMinistry of Natural Resources and Forestry
FundersHuazhong Agricultural UniversityChinese Academy of Sciences
KeywordsGrass carpStockingAquacultureFisheryBiologyEcologyChinaHydrillaInvasive speciesCarpAquatic plantGeographyMacrophyteFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract Grass Carp Ctenopharyngodon idella was introduced to the southern United States in the 1960s to control aquatic macrophytes in aquaculture ponds. The accidental release of Grass Carp from some research facilities and aquaculture farms at the start of the introduction, followed by the broad promotion of stocking triploid and diploid fish, helped to facilitate the expansion of the invasive range of the species in North America. Grass Carp have recently been observed to reproduce in Lake Erie. The species has been an important food fish in China for centuries, and Chinese scientists and government agencies have accumulated a great deal of experience, knowledge, and data on Grass Carp. We review Chinese literature and provide a synthesis of the biology and ecology of Grass Carp in China, including the native geographic distribution as well as the factors that determine its reproductive success, growth, and foraging behavior. We also review the impacts of the introduction (or invasion) of Grass Carp on receiving systems and the effects of dams and pollution on Grass Carp. This review fills knowledge gaps in the Western scientific literature about Grass Carp. It provides scientific information that could be used to guide future research and management on ways to control the invasion and propagation of this species.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.867
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.010
GPT teacher head0.247
Teacher spread0.237 · 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 designOther design
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

Citations47
Published2020
Admission routes1
Has abstractyes

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