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Record W6888887483 · doi:10.22124/cjes.2023.6491

''Transboundary river water quality as a core indicator for sustainable environmental development in Europe: A case study between republics of Bulgaria and Serbia''

2023· article· en· W6888887483 on OpenAlexaboutno aff

Bibliographic record

VenueBulgarian Portal for Open Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater Framework DirectiveSustainable developmentWater qualityWater resourcesSustainabilityQuality (philosophy)Environmental qualityBulgarian

Abstract

fetched live from OpenAlex

In recent years, the issue of the sustainable management and protection of water resources has gained increasing emphasis in environmental policies at the local, national and supranational levels. The goal of the present study is the analysis and assessment of water quality in the Bulgarian section of the Timok, Nishava and Erma (Jerma) rivers for the period 2015-2021. The quality status of the studied river courses was assessed by the values of ten physicochemical indicators and the concentrations of eight heavy metals. The analysis and assessment performed were based on the Water Act (WA) in accordance with the criteria by Directive 2000/60/EC or so called Water Framework Directive. The Canadian Water Quality Index (CWQI) was applied for the analysis. Achieving the goal formulated in the study could serve as a good basis for making informed management decisions.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.073
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.000
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 head0.069
GPT teacher head0.363
Teacher spread0.294 · 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 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
Published2023
Admission routes1
Has abstractyes

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