MétaCan
Menu
Back to cohort
Record W2965160631 · doi:10.1134/s1875372819020045

Comparing the Efficiency of River Water Quality Parameterization by Different Methods Under a Significant Human-Induced Impact

2019· article· en· W2965160631 on OpenAlexaboutno aff
M. B. Zaslavskaya, Oxana Erina, Л. Е. Ефимова

Bibliographic record

VenueGeography and Natural Resources · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityEnvironmental scienceHydrometeorologyAquatic ecosystemPollutionScale (ratio)Hydrology (agriculture)STREAMSQuality (philosophy)EcosystemWater resource managementEcologyGeographyMeteorologyPrecipitationComputer scienceGeologyBiology

Abstract

fetched live from OpenAlex

We examine the different approaches in assessing the water quality of water bodies located within the territories with a significant human-induced impact. The hydrological region of Norilsk was used as a test site. The data used in the analysis characterize the period between 2001 and 2003; however, they are still relevant because of a high level of human-induced impact on water bodies. For the purposes of parameterization, the water quality indices which are being most abundantly used in Russia and abroad were evaluated. Results from parameterizing the water quality, obtained by various methods and combined into an overall scheme, were used to generate the rating scale for assessing the hydro-ecological status of aquatic ecosystems. These calculations show that the method of Specific Combinatorial Water Pollution Index (SCWPI) established by the departmental standard of the Federal Service for Hydrometeorology and Environmental Monitoring of Russia (Rosgidromet) provides the most objective water quality assessment for water bodies experiencing a significant human-induced impact. Similar results also apply for water quality parameterization using the Canadian CCME WQI method, which is confirmed by the closeness of correlation between the values of these indices. According to the SCWPI method, in none of the streams was the hydro-ecological status assessed as “normal”. In the sources of four rivers, it was found to be close to class 1, and their hydro-ecological status was assessed as “risk”. The water in 11 measuring sections corresponds to quality class 3, or a “critical” status of the aquatic ecosystem. In 12 measuring sections corresponding mainly to the estuarine segments of the rivers and some brooks, the hydro-ecological status of the1 water bodies is characterized as “disaster”, i. e. the water pertains to quality class 4 and 5. Furthermore, in none of the water bodies under study is the environmental “catastrophe” not recorded.

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.030
GPT teacher head0.334
Teacher spread0.304 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueGeography and Natural ResourcesSame topicWater Quality and Pollution AssessmentFrench-language works237,207