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Experimental and numerical study of wastewater pollution in Yuhui channel, Jiashan city

2018· article· en· W2793737402 on OpenAlexaff
Lei Fu, Zhenhua Peng, Aiju You

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum chaos and dynamical systems
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsWastewaterEnvironmental sciencePollutantChannel (broadcasting)Sewage treatmentPollutionChinaEnvironmental engineeringWaste managementEngineeringGeographyTelecommunications

Abstract

fetched live from OpenAlex

Due to the development of economics and society in China, the huge amount of wastewater becomes a serious problem in most of the Chinese cities. Therefore, the construction of wastewater treatment plant draws much more attentions than before. The discharge from the wastewater treatment plant is then considered as a point source in most of the important rivers and channels in China. In this study, a typical wastewater treatment plant extension project is introduced as a case study, a filed monitoring experiment is designed and executed to observe required data, then, a two-dimensional model is estabilished to simulate the water quality downsteam of the wastewater treatment plant, COD Cr is considered as a typical pollutant during the simulation. The simulation results indicate that different discharge conditions will lead to different COD Cr concentration downstream of the wastewater treatment plant, and an emergency plan should be prepared to minimize the risk of the pollution in the channel under unusual and accident conditions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.224
Teacher spread0.211 · 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 designSimulation or modeling
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
Published2018
Admission routes1
Has abstractyes

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