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Record W2259731919 · doi:10.1680/wama.14.00134

Impacts of biological activities on erosion of sewer sediments

2015· article· en· W2259731919 on OpenAlexaff
Yongchao Zhou, Yan Ma, Lei Fang, Yiping Guo

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Water Management · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsMcMaster University
FundersNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsErosionSedimentEnvironmental scienceConsolidation (business)Sediment transportHydrology (agriculture)GeologyEnvironmental engineeringSoil scienceGeotechnical engineeringGeomorphology

Abstract

fetched live from OpenAlex

Experimental studies were conducted to investigate the influences of biological processes on the erosion behaviour of organic-rich sanitary sewer sediments. The results show that biological activities can make sediments expand and their bulk densities decrease. The experimental results also illustrate that sewer sediment erosion is a very complex process influenced by gravitational consolidation and biostabilisation. Aerobic biological processes can weaken a sediment bed and affect the erosion patterns for sediments rich in volatile solids, whereas the same processes can increase the resistance to erosion of sediments with lower volatile solid contents. Under anaerobic conditions, two sediment layers with different physical properties and erosion-resistance capabilities would form as a result of biological activities. Under low temperature and aerobic conditions, however, gravitational consolidation was identified as the major factor controlling the erosion behaviour of 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.160

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 head0.026
GPT teacher head0.208
Teacher spread0.182 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

Explore more

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