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Record W2337487577 · doi:10.14393/19834071.2015.30122

Comparação entre dois métodos para determinação da qualidade da água tratada

2016· article· pt· W2337487577 on OpenAlexaboutno aff
Neemias Cintra Fernandes, Paulo Sérgio Scalize

Bibliographic record

VenueCiência & Engenharia · 2016
Typearticle
Languagept
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityEnvironmental sciencePopulationWet seasonWater consumptionMathematicsEnvironmental engineeringGeographyEcologyBiologyDemographyCartography

Abstract

fetched live from OpenAlex

The assessment of water quality destined to population consumption is something essential; for this reason the physical, chemical and bacteriological parameters are monitored and must be according to the limits established in legislation. Thus, the present study has determined and compared the application of two Water Quality Indexes (WQI) of 249 treated water samples, collected in the water supply system of the city of Goiania, during a period of 24 months. These samples were subjected to analysis of 10 physical-chemical parameters and 3 microbiological parameters. The WQI values for the samples were determined using a Canadian WQI calculation model, and also by using different calculation model, employed by the local State Company. The results indicated that the water distributed in 88.8% of the samples were rated as excellent by the two models, indicating that the model employed by local State Company is more restrictive than the Canadian model, besides that there is a seasonal influences pointing to a worse water classification in the rainy season. Keywords: WQI, Water quality, Canadian model.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.153
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
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 head0.087
GPT teacher head0.327
Teacher spread0.241 · 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 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

Citations4
Published2016
Admission routes1
Has abstractyes

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