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Record W2055071838 · doi:10.1371/journal.pone.0027001

Classification of Sharks in the Egyptian Mediterranean Waters Using Morphological and DNA Barcoding Approaches

2011· article· en· W2055071838 on OpenAlexfundno aff
Marie Moftah, Sayeda H. Abdel Aziz, Sara Elramah, Alexandre Favereaux

Bibliographic record

VenuePLoS ONE · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsDNA barcodingScyliorhinus caniculaBiologyChondrichthyesMitochondrial DNAPhylogenetic treeZoologyCarcharhinusBiodiversityEvolutionary biologyEcologyFisheryGeneGenetics

Abstract

fetched live from OpenAlex

The identification of species constitutes the first basic step in phylogenetic studies, biodiversity monitoring and conservation. DNA barcoding, i.e. the sequencing of a short standardized region of DNA, has been proposed as a new tool for animal species identification. The present study provides an update on the composition of shark in the Egyptian Mediterranean waters off Alexandria, since the latest study to date was performed 30 years ago, DNA barcoding was used in addition to classical taxonomical methodologies. Thus, 51 specimen were DNA barcoded for a 667 bp region of the mitochondrial COI gene. Although DNA barcoding aims at developing species identification systems, some phylogenetic signals were apparent in the data. In the neighbor-joining tree, 8 major clusters were apparent, each of them containing individuals belonging to the same species, and most with 100% bootstrap value. This study is the first to our knowledge to use DNA barcoding of the mitochondrial COI gene in order to confirm the presence of species Squalus acanthias, Oxynotus centrina, Squatina squatina, Scyliorhinus canicula, Scyliorhinus stellaris, Mustelus mustelus, Mustelus punctulatus and Carcharhinus altimus in the Egyptian Mediterranean waters. Finally, our study is the starting point of a new barcoding database concerning shark composition in the Egyptian Mediterranean waters (Barcoding of Egyptian Mediterranean Sharks [BEMS], http://www.boldsystems.org/views/projectlist.php?&#Barcoding%20Fish%20%28FishBOL%29).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.357
GPT teacher head0.277
Teacher spread0.079 · 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 designBench or experimental
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

Citations34
Published2011
Admission routes1
Has abstractyes

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