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Record W2095189374 · doi:10.2166/wst.2011.091

Evaluation of biofilm performance as a protective barrier against biocorrosion using an enzyme electrode

2011· article· en· W2095189374 on OpenAlexaff
Sahar Soleimani, Banu Örmeci, O. Burkan Isgor, Sankara Papavinasam

Bibliographic record

VenueWater Science & Technology · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsNatural Resources CanadaCarleton University
FundersTexas A and M University
KeywordsBiofilmSulfideChemistryMicrobiologyEscherichia coliWastewaterAmperometryBacteriaElectrodeEnvironmental engineeringBiologyEnvironmental scienceElectrochemistryBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Sulfide is known to be an important factor in microbiologically influenced corrosion (MIC) of metals and concrete deterioration in wastewater treatment structures and sewer pipelines. A sulfide biosensor was used to determine the effectiveness of Escherichia coli DH5 alpha biofilm as a protective barrier against MIC. The biofilm was shown to be effective in protecting surfaces from sulfide and helping to reduce MIC using amperometric measurements. The results also indicated that the growth conditions of E. coli DH5 alpha may have an impact on the performance of the biofilm as a sulfide barrier. The simple method provided in this work enables the comparison of several microbial biofilms and selection of the ones with potential to prevent MIC in a relatively short time.

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)0.003
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 score0.011
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.054
GPT teacher head0.292
Teacher spread0.238 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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