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Record W2990299569 · doi:10.26583/gns-2019-01-02

WATER QUALITY ASSESSMENT ON SANITARY-HYGIENIC PARAMETERS OF NEMAN RIVER AT BALTIC POWER PLANT (UNDER CONSTRUCTION) REGION

2019· article· en· W2990299569 on OpenAlexaff
E. V. Luneva, E.A. Vereshchagina, D. V. Kulakov, M. E. Makushenko

Bibliographic record

VenueGlobal Nuclear Safety · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsSt. Peter's Hospital
Fundersnot available
KeywordsEnvironmental scienceWater qualityWater resource managementQuality (philosophy)Baltic seaEnvironmental engineeringGeologyBiologyEcologyOceanography

Abstract

fetched live from OpenAlex

Using surface water objects for water supply and disposal systems of nuclear power plants (NPP) produces a complex of problems concerned with environmental and health protection. Sanitary-hygienic (including hydrochemical and micro-biological) parameters and natural water toxicity are studied at Neman river, as the river is planned to be a cooling pond of Baltic NPP, which is under construction. Water quality assessment is done based on the observed data during 2011–2016. Observations have shown high variety of river condition during the year (seasonal variations) with not good enough water quality parameters for water supply purposes over the most part of the year. To obtain water with high organoleptic indicators and an acceptable level of risk in terms of chemical and microbiological composition for water supply system, a complex of methods for water purification, post-treatment and disinfection should be applied. Although, it is shown, that natural waters of the Neman river within the Kaliningrad region should be considered not to have a toxic effect on aquatic organisms.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.999

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)0.0060.002

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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