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Water Quality Assessment of Danjiangkou Reservoir and its Tributaries in China

2018· article· en· W2789731088 on OpenAlexaboutno aff
Linghua Liu, Wenqi Peng, Leixiang Wu, Laisheng Liu

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
FundersMajor Science and Technology Program for Water Pollution Control and TreatmentInternational Science and Technology Center
KeywordsTributaryWater qualityEnvironmental scienceHydrology (agriculture)Fecal coliformGeologyGeographyEcology

Abstract

fetched live from OpenAlex

Danjiangkou Reservoir is an important water source for the middle route of the South to North Water Diversion Project in China, and water quality of Danjiangkou Reservoir and its tributaries is crucial for the project. The purpose of this study is to evaluate the water quality of Daniiangkou Reservoir and its tributaries based on Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI). 22 water quality parameters from 25 sampling sites were analyzed to calculate WQI. The results indicate that water quality in Danjiangkou Reservoir area, Hanjiang River and Danjiang River is excellent. And the seriously polluted tributary rivers were Shending River, Jianghe River, Sihe River, Tianhe River, Jianhe River and Jiangjun River. Water quality parameters that cannot meet the standard limit for drinking water source were fecal coliform bacteria, CODcr, CODMn, BOD5, NH3-N, TP, DO, anionic surfactant and petroleum. Fecal coliform bacteria, TP, ammonia nitrogen, CODMn were the most common parameters to fail.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
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 score0.632
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.286
Teacher spread0.252 · 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 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

Citations11
Published2018
Admission routes1
Has abstractyes

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