MétaCan
Menu
Back to cohort
Record W2526050260 · doi:10.2495/sdp-v11-n6-1037-1043

Water quality index in an Urban Watershed

2016· article· en· W2526050260 on OpenAlexvenueno aff
Raissa C. Gomes, Regina Márcia Longo, Fernando H.S. Ribeiro, Sueli do Carmo Bettine, Antônio Carlos Demanboro, Admilson ́Írio Ribeiro

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWatershedIndex (typography)Water qualityEnvironmental scienceWater resource managementQuality (philosophy)Environmental planningHydrology (agriculture)Computer scienceEngineeringEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

This study aimed to verify the water quality of Ribeiro das Pedras (Stones River), Campinas, So Paulo, Brazil through the implementation of the Water Quality Index (WQI) and comparison with Brazilian legislation (Resolution of the National Environment Council -CONAMA 357/2005), thus being able to initiate discussions about anthropic interferences in watercourses located in urban areas. Ribeiro das Pedras is part of an urban watershed that suffered, and still suffers, from the rapid and intense urban and housing boom, finding its territorial space almost fully occupied. For the execution of this work, six sample points were defined in order to allow a discussion between the land use within their respective drainage area and the results of the WQI applications. The WQI is composed of nine parameters: dissolved oxygen, biochemical oxygen demand, nitrogen, temperature, thermotolerant coliforms, turbidity, phosphorus, pH, and total solids. The first sample point refers to the main watercourse source, four sample points are located throughout the watershed and the last point is located in its base level, at the confluence between Ribeiro das Pedras and its main stem, Ribeiro das Anhumas (Anhumas River). The results of water quality analysis obtained based on the WQI concept were featured as 'GOOD'; however, the isolated analysis of each parameter allows to compare them with the Brazilian legislation, where it appears that none of the points meets all established quality parameters. Thus, it can be concluded that the watercourse suffers significant impacts along its course, probably derived from the use of the surrounding drainage areas.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.478

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.299
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Sustainable Development and PlanningSame topicWater Quality and Pollution AssessmentFrench-language works237,207