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Record W4392892830 · doi:10.34119/bjhrv7n2-099

Contaminantes em peixes provenientes dos rios paraná e tietê: um grave problema ambiental e de saúde pública

2024· article· pt· W4392892830 on OpenAlexaff
Willian Marinho Dourado Coelho, João Felipe Azambuja de Freitas, Luiz Henrique Ferreira dos Santos, Patrícia Raquel Basso Rosa, Silvia Maria Marinho Storti

Bibliographic record

VenueBrazilian Journal of Health Review · 2024
Typearticle
Languagept
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsQUAD Engineering (Canada)
Fundersnot available
KeywordsHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

As enfermidades transmitidas por alimentos aquáticos são causadas por diversos tipos de agentes biológicos e tóxicos que são transmitidos aos seres humanos e animais através do consumo de peixes, moluscos e crustáceos dentre outros. O objetivo desta pesquisa foi relatar a ocorrência de contaminantes de origem orgânica e inorgânica em peixes provenientes dos rios Tietê e Paraná, SP. Foram isolados numerosos agentes bacterianos como Listeria spp., Escherichia coli, Salmonella spp., Shigella spp., Proteus spp., Vibrio vulnificus, Edwardsiella spp., Aeromonas spp. e também contaminantes químicos como hidrocarbonetos clorados, cádmio e chumbo. A partir dos resultados obtidos nesta pesquisas pode-se verificar a ocorrência de grande número de microorganismos patogênicos e de produtos químicos em peixes provenientes dos rios Paraná e Tiete – SP, ficando evidenciado que a contaminação das águas por efluentes domésticos, industriais e da ceva proveniente da atividade pesqueira ocorre nestas áreas, gerando risco ao meio ambiente e à saúde única.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.588
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.326
Teacher spread0.299 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBrazilian Journal of Health ReviewSame topicFish biology, ecology, and behaviorFrench-language works237,207