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Record W4318001663 · doi:10.26507/paper.2239

An overview of water quality regulation or standards in swimming pools, drinking water, and hot springs in Germany, Canada, and Colombia

2022· article· es· W4318001663 on OpenAlexaffabout
Yuly Andrea Sánchez Londoño, Mehrab Mehrvar, Lynda H. McCarthy, Édgar Quiñones, Luis Eduardo Rodríguez Cheu, Alexander Reuß, Jairo Romero

Bibliographic record

VenueEncuentro Internacional de Educación en Ingeniería · 2022
Typearticle
Languagees
FieldEnvironmental Science
TopicEnvironmental and Cultural Studies in Latin America and Beyond
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPotable waterHumanitiesPolitical scienceGeographyPhysicsArtEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

Este artículo detalla las regulaciones en la calidad del agua en piscinas y agua potable en Alemania, Canadá y Colombia, con una comparación con la regulación existente y los estándares de calidad de las aguas termales. Canadá, Alemania y Colombia regulan que el agua potable debe estar libre de niveles inseguros de sustancias y patógenos, especificando los parámetros microbiológicos y químicos que deben seguirse. Las piscinas en Canadá, Alemania y Colombia tienen regulaciones o estándares específicos para parámetros microbiológicos y químicos que deben seguirse. Al igual que la regulación del agua potable, el agua debe estar libre de organismos patógenos para conservar su calidad de agua. Por otro lado, en el caso de aguas termales donde el bañista tiene condiciones similares a las de las piscinas, Canadá y Alemania no cuentan con regulaciones o normas específicas para el agua de aguas termales. En cambio, se aplican a las aguas termales los mismos requisitos microbianos y químicos que para el agua de piscinas según la Normativa de piscinas públicas de Canadá y la norma Din 19643 de Alemania. Actualmente, Colombia no cuenta con reglamentos o normas sobre la calidad de las aguas termales, tal como lo establece el artículo 6 del Decreto 554 de 2015.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.286
Teacher spread0.272 · 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 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
Published2022
Admission routes2
Has abstractyes

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