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Record W4389331630 · doi:10.21168/rega.v20e23

Situação de corpos hídricos em bacias hidrográficas do Rio Grande do Sul sob a perspectiva do Índice de Conformidade ao Enquadramento (ICE)

2023· article· pt· W4389331630 on OpenAlex
Sumirê Hinata, Aline Kaliski, Claudia Wolff, Fernando Comerlato Scottá, Raíza Cristóvão Schuster, Walter Souza, Luciano Cardone

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRevista de Gestão de Água da América Latina · 2023
Typearticle
Languagept
FieldEnvironmental Science
TopicGeography and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeology

Abstract

fetched live from OpenAlex

O enquadramento de corpos hídricos é um importante instrumento para o acompanhamento da situação da qualidade da água. Avaliar e informar a distância na qual os principais cursos d-água se encontram em relação às metas pretendidas pelo enquadramento constitui-se em uma forma de avaliação profícua, mas normalmente pouco realizada. Esse estudo se propõe a aplicar a metodologia do Índice de Conformidade ao Enquadramento (ICE), desenvolvida pelo Canadian Council of Ministers of the Environment (CCME), em 172 estações em 19 bacias hidrográficas no Rio Grande do Sul, no período de 2015 a 2022. O estudo considerou 13 parâmetros definidos na Resolução CONAMA Nº 357/2005. Os resultados indicaram que 45% das estações observadas ficaram com índice -razoável-, seguido de 41% com índice -marginal-, com resultados comprometidos principalmente pelos parâmetros cádmio, E. coli, ferro, fósforo, manganês e OD. O ICE se mostrou uma ferramenta adequada para informar de forma eficaz aos gestores e atores envolvidos a condição dos corpos hídricos de forma geral e realizar comparações entre bacias distintas.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient 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 score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.019
GPT teacher head0.257
Teacher spread0.239 · 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