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Mangrove oyster (Crassostrea rhizophorae) (Guilding, 1928) farming areas as artificial reefs for fish: A case study in the State of Ceará, Brazil

2006· article· en· W1504152722 on OpenAlexfundno aff
Luiz Eduardo Lima de Freitas, Caroline Vieira Feitosa, Maria Elisabeth de Araújo

Bibliographic record

VenueBrazilian Journal of Oceanography · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
FundersUniversidade de PernambucoUniversidade Federal de PernambucoUniversity of Alberta
KeywordsMangroveOysterFisheryTransectAquacultureReefBiologyCrassostreaEcologyAbundance (ecology)Fish <Actinopterygii>

Abstract

fetched live from OpenAlex

A type of platform, known as a table, is now being used for mangrove oyster farming. In Fortim, Ceará, Brazil, this activity was begun in June 2000 and covers an area of 50 m² overlying a sand-clay substrate. The present study has the following main objectives: to identify and catalogue the ichthyofauna colonizing the Crassostrea rhizophorae farming platforms; to evaluate ecological aspects, such as the possible correlation between the physical and chemical variables for water quality and the occurrence of the ichthyofauna; and to observe the differences in the fish species found during tidal variations. Specimens were identified and quantified using the linear-transect, visual census methodology. The ichthyofauna observed comprised 3,030 individuals belonging to 28 species and 20 families. Of the 28 species found in the area studied, 14 were marine transients, 12 marine dependent, and only 2 permanent residents. A significant association was observed between the abundance of 11 species and the physical and chemical variables studied. Based on these results, it may be concluded that the platforms act as artificial reefs for the ichthyofauna, being colonized by at least 28 species, and providing protection from predators as well as a source of food and a reproductive substrate.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

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