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Record W2115747014 · doi:10.2298/abs1104209k

The anthropogenic impact on water quality of the river Danube in Serbia: Microbiological analysis and genotoxicity monitoring

2011· article· en· W2115747014 on OpenAlexaff
Stoimir Kolarević, Jelena Knežević‐Vukčević, Momír Paunović, Jelena Tomović, Branka Vuković‐Gačić

Bibliographic record

VenueArchives of Biological Sciences · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsGenotoxicityFecal coliformEnvironmental scienceWater qualityContaminationEnvironmental chemistryMercury (programming language)Comet assaySedimentPollutionEcotoxicologyVeterinary medicineBiologyEcologyChemistryDNA damageToxicity

Abstract

fetched live from OpenAlex

The aim of this work was to examine the impact of urban wastewaters on the water quality of the Danube River in Serbia. Samples of water and sediments for microbiological analysis and genotoxicity monitoring were collected from 6 sites during spring and/or autumn 2010. Sanitary analysis, i.e. enumeration of total and fecal coliforms and intestinal enterococci, indicated moderate to critical fecal contamination, while organic load assessment (oligotroph to heterotroph ratio, index of phosphatase activity) revealed the category of moderately polluted water. Mercury-resistant bacteria were detected in all water samples, with high numbers at locations positioned downstream of Belgrade. There was no correlation of the microbiological parameters of the sediment and water samples. Genotoxicity monitoring, performed by the comet assay on hemocytes of mussels Sinanodonta woodiana, indicated a significant increase of DNA damage in mussels collected from the studied sites compared with the control group.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.995

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 studies0.0000.007
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.090
GPT teacher head0.338
Teacher spread0.247 · 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

Citations38
Published2011
Admission routes1
Has abstractyes

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