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Record W7034953179

Who is the better candidate? Macroinvertebrates and diatoms for ecological status assessment of Sava Lake (Serbia)

2021· article· en· W7034953179 on OpenAlexfundno aff

Bibliographic record

VenueCER (University of Belgrade, Institute of Chemistry, Technology and Metallurgy) · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
FundersLeibniz-Institut für Gewässerökologie und BinnenfischereiUniversität InnsbruckUppsala UniversitetBulgarian Academy of SciencesUniversità degli Studi di TorinoUniversité de GenèveInstitut National de Recherche en Sciences et Technologies pour l'Environnement et l'AgricultureUniversitat de BarcelonaUmeå UniversitetSveriges LantbruksuniversitetLeibniz-GemeinschaftUniversidade de LisboaUniversitat de GironaCanadian Institute for Advanced ResearchUniversidade do PortoBournemouth University
KeywordsNucleofectionExclosureLimitingGestational period
DOInot available

Abstract

fetched live from OpenAlex

Sava Lake was created from the right arm of the Sava River, and the inhabitants of Belgrade use the lake intensively for swimming and bathing. We analysed macrozoobenthos and epilithic diatom communities at six sites from April to October 2017, to assess the ecological status of Sava Lake according to the National legislation of Serbia. Considering macrozoobenthos communities, the mean values of Zelinka and Marvan saprobity index indicated high ecological status. In contrast, results obtained from the mean values of BMWP (Biological Monitoring Working Party) scores suggested moderate to poor ecological status. The mean values of the IPS diatom index (Indice de Polluo-sensibilité) indicated high ecological status, while the TDIL index (Trophic Diatom Index for lakes) was slightly more sensitive and indicated good ecological status. Water chemical parameters indicated that Sava Lake was mainly oligotrophic during the study period (average total phosphorus concentrations were 10.7 μgL-1 and average total nitrogen concentrations 410 μgL-1). Before being able to adopt an integrative approach for ecological status assessment (combining two or more biological quality elements), more studies must be performed on how to choose the most sensitive and adequate indices. This is especially true for lakes experiencing intensive anthropogenic pressure during the summer season. Also, the boundary values in the National legislation of Serbia must be adapted for lakes, such as Sava Lake.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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 designTheoretical or conceptual
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

Citations0
Published2021
Admission routes1
Has abstractyes

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