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Record W4409228239 · doi:10.1590/1809-4392202301761

Incidental capture and diversity of Elasmobranchii and Teleostei caught by red snapper and lobster fisheries in the Great Amazon Reef System

2025· article· en· W4409228239 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueActa Amazonica · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsUniversity of Regina
FundersFundação de Apoio à Pesquisa do Estado da Paraíba
KeywordsFisheryTeleosteiElasmobranchiiReefAmazon rainforestGeographyFish <Actinopterygii>BiologyEcology

Abstract

fetched live from OpenAlex

ABSTRACT The Great Amazon Reef System is one of the least known mesophotic environments on the Atlantic coast of northern South America, threatened by oil and gas exploration projects and explored by different industrial fisheries. Here, we provide the first inventory of the cartilaginous and bony fishes captured by industrial fisheries of the red snapper and lobster in the Great Amazonian Reef System, including a list of species with ecological and conservation information, in addition to biogeographic considerations. A total of 143 species were recorded, with 17 elasmobranchs and 126 teleosts. A specimen likely representing a hybrid between Cephalopholis fulva and Cephalopholis furcifer (Serranidae) was also recorded. Community ecology descriptors were employed to explore the diversity patterns of the species captured by different fishing gears. Our results highlight the relevance of monitoring fishery activities to enhance knowledge of the biodiversity in poorly sampled areas and understanding the local impacts of human activities.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.310

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 studies0.0000.001
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 head0.004
GPT teacher head0.180
Teacher spread0.177 · 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