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Record W1788380808

APLICAÇÃO DA TÉCNICA DE ELETROCINESE PARA REMEDIAÇÃO DE METAIS NA ÁGUA SUBTERRÂNEA

2011· article· pt· W1788380808 on OpenAlexaff
Lilian Puerta Machado Silveira, José Eustáquio Machado, Leandro Ferreira de Freitas, Ana Paula Spolidoro Queiroz, Lina Yamawaki, Sérgio Shigueo Kurozawa

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2011
Typearticle
Languagept
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsRegional Municipality of Waterloo
Fundersnot available
KeywordsPhysicsHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

A técnica de eletrocinese é uma opção para remediação em locais impactados por metais pesados e consiste na aplicação de corrente elétrica em dois eletrodos produzindo um campo elétrico que atrai íons de cargas opostas as dos eletrodos. O presente trabalho teve como objetivo testar a aplicabilidade desta técnica em uma área impactada por metais em um aqüífero com baixa condutividade hidráulica. O ensaio foi avaliado quanto a três linhas de evidência: ocorrência dos processos físico-químicos esperados, redução da concentração dos metais e quanto a massa removida. Os resultados corresponderam às expectativas das três linhas de evidência, sendo identificados resultados satisfatórios na remoção de Al, Ni, Cu, Cr, Zn, Mn e Fe e uma taxa de remoção de 180 g/h, indicando ser uma técnica promissora na remediação de águas subterrâneas.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

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 integrity0.0010.000
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 head0.036
GPT teacher head0.255
Teacher spread0.219 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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