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Record W1125058691

100 лет законодательного регулирования качества питьевой воды. Ретроспектива, современное состояние и перспективы

2014· article· ru· W1125058691 on OpenAlexaboutno aff
Рахманин Юрий Анатольевич, Красовский Гурий Николаевич, Егорова Наталия Александровна, Михайлова Руфина Иринарховна

Bibliographic record

VenueГигиена и санитария · 2014
Typearticle
Languageru
FieldMedicine
TopicHuman Health and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsHarmonizationNormativeStandardizationEnvironmental planningPopulationLegislatureWater qualityEnvironmental protectionLegislationBusinessChinaEnvironmental scienceNatural resource economicsPolitical scienceEnvironmental healthLawEconomicsEcology
DOInot available

Abstract

fetched live from OpenAlex

There is considered the history of the development of legislative requirements to the regulation of the quality of drinking water in different countries and international organizations during the period from 1912 to the present time. In terms of comparative analysis there is analyzed the current state of regulatory frameworks of the Russian Federation, WHO, EU, Finland, the UK, Singapore, Australia, Japan, China, Nigeria, the United States and Canada in the field of providing favorable conditions of population drinking water use. There has been noted the significant progress in standardization of the content of the biogenic elements and chemical pollution of drinking water in the absence of uniform requirements to the composition and properties of drinking water globally, that is bound to the need to take into account the national peculiarities of drinking water supply within the separate countries. As promising directions for improving regulation of drinking water quality there are noted: the development of new standards for prioritized water pollution, periodic review of standards after appearance of the new scientific data on the biological action of substances, the use of the concept of risk, the harmonization of the normative values and the assessment of the possibility of introduction into the practice the one more criterion of profitableness of population water use the bioenergetic state of the water

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0270.036

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 head0.029
GPT teacher head0.343
Teacher spread0.315 · 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 designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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