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Record W2460174469 · doi:10.21168/rbrh.v16n2.p13-24

Variação das Características Hidráulicas em Condutos Forçados Operando sob Condições de Infestação por Limnoperna fortunei

2011· article· pt· W2460174469 on OpenAlexaff
CLAUDIA SIMEÃO, MARCIO RESENDE, CARLOS MARTINEZ

Bibliographic record

VenueRevista Brasileira de Recursos Hídricos · 2011
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

O mexilhão dourado vem causando grandes prejuízos ambientais e econômicos em diversos locais no Brasil.Vivendo aglomerados e possuindo uma estrutura protéica de forte fixação, os indivíduos formam camadas no interior de tubulações, bombas, filtros e sistemas de refrigeração, provocando um substancial aumento da perda de carga nos sistemas e chegando a provocar entupimento dos mesmos.Este trabalho apresenta os estudos experimentais destinados à determinação de coeficientes de perda de carga de tubulações forçadas, submetidas ao efeito progressivo da incrustação de mexilhões dourados em seu interior.Os ensaios foram realizados em tubulações com diâmetros de 2; 2,50; 3 e 4 polegadas, com taxas de infestação de 0, 0.5 e 1.0 indivíduos./cm 2 .Os resultados obtidos indicaram que o aumento de rugosidade e a perda de seção útil devido à infestação promoveram acréscimos significativos nas perdas de carga distribuídas.Para cenários de infestação na densidade de 0,5 indivíduo/cm² obteve-se um acréscimo de perda de carga entre 0,5 e 3 vezes superiores àquelas obtidas nos tubos sem infestação.Para o para o cenário de infestação na densidade de 1,0 indivíduo/cm², os acréscimos foram de 10 a 90 vezes superiores àquelas obtidas nos tubos sem infestação.Nesses casos a capacidades de escoamento correspondem, respectivamente, a cerca de 60% e 20% da vazão original.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.301
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 source (direct Gemma or distilled Codex), 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

Citations2
Published2011
Admission routes1
Has abstractyes

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