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Record W1986808253 · doi:10.1520/jai102185

Effect of Contaminated Suspended Solids on Water and Sediment Qualities and Their Treatment

2009· article· en· W1986808253 on OpenAlexaffabout
Tomohiro Inoue, Catherine N. Mulligan, Ehsan M. Zadeh, Masaharu Fukue

Bibliographic record

VenueJournal of ASTM International · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsConcordia University
Fundersnot available
KeywordsSedimentFiltration (mathematics)SedimentationWater qualitySuspended solidsContaminationTotal suspended solidsEnvironmental scienceEnvironmental chemistryPhosphorusFilter (signal processing)AdsorptionNutrientTurbidityEnvironmental engineeringChemical oxygen demandChemistryGeologySewage treatmentWastewaterEcology

Abstract

fetched live from OpenAlex

Abstract Suspended solids (SS) have been discharged into water areas such as rivers, lakes, and ponds. The SS adsorb various contaminants such as heavy metals and nutrients and also form sediments by sedimentation. Therefore, contaminated SS will be able to influence not only the water quality, but also the sediment quality. In order to understand the effect of contaminated SS on the water and the sediment, SS and sediment samples were obtained from the des Hurons River in Canada. In addition, laboratory filtration tests were performed to develop a technique for removal of the SS. A downward filtration system was used with a nonwoven geotextile as a filter medium. The apparent opening size (AOS) and the thickness of the filter were 150 μm and 0.2 cm, respectively. For the investigation, the results showed that both SS and the sediments contained heavy metals with concentrations in the SS higher. In particular, zinc concentrations of the SS were approximately from two to five times higher than the Canadian guideline for sediments. In addition, it was found that SS concentrations were associated with chemical oxygen demand (COD) and total phosphorus (T-P) concentrations. Therefore, it was found that SS can play an important role in the water and the sediment qualities. The laboratory filtration tests showed the SS were reduced from 32 mg/L to 2 mg/L or less by the nonwoven filter. Thus, SS removal will improve not only the water quality, but also the quality of the bottom sediments.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.520

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.237
Teacher spread0.232 · 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

Citations8
Published2009
Admission routes2
Has abstractyes

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