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Record W1982859012 · doi:10.2136/vzj2014.07.0086

Impact of Bioclogging on Peat vs. Sand Biofilters

2015· article· en· W1982859012 on OpenAlexaff
M. Mostafa, Paul J. Van Geel

Bibliographic record

VenueVadose Zone Journal · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCloggingBiofilterPeatEnvironmental scienceSoil waterSeptic tankDrainageBiomass (ecology)Environmental engineeringVadose zoneSoil scienceGeologyEcology

Abstract

fetched live from OpenAlex

Biological clogging of unsaturated soils is an important process that can lead to the development of a biomat and failure of biofilters used to treat various wastewater streams. Septic beds and peat filters used to treat septic tank effluent are important applications. Several conceptual models have been developed to simulate clogging in saturated soils; however, limited effort has been conducted to develop similar models for unsaturated soils. Different conceptual models have been proposed to simulate biological clogging in unsaturated systems. These models include the impacts of biomass growth on the relative permeability term for unsaturated flow, but limited experimental data have been used to validate these models. In this study, column experiments were conducted to study the clogging process in loose and dense peat, filter media sand, and septic bed sand. Experimental data indicated that the pore structure of the peat, in comparison to two commonly used sands for septic drainage fields, allowed the biomass to distribute itself over a greater depth within the peat biofilter and delayed the formation of a biomat at the surface and eventual clogging of the filter medium.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score1.000

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)0.0010.000

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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.

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

Citations7
Published2015
Admission routes1
Has abstractyes

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