MétaCan
Menu
Back to cohort
Record W7097045712

SEE PROFILE

2016· article· en· W7097045712 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityQuality (philosophy)Waterborne diseasesSampling (signal processing)Water supply
DOInot available

Abstract

fetched live from OpenAlex

Abstract: Problem statement: The quality of drinking water is a crucial factor for human health. The objective of this study was the assessment of physical, chemical and bacteriological quality of the drinking water in the city of Tetova and several surrounding villages in the Republic of Macedonia for the period May 2007-2008. The sampling and analysis are conducted in accordance with State Regulation No. 57/2004, which is in compliance with EU and WHO standards. A total of 415 samples were taken for chemical, physical and bacteriological analysis. Approach: We had used the Canadian Drinking Water Quality Index (DWQI) for the quality assessment of drinking water. Results: The results of the samples taken in Tetova point to better hygienic and sanitary conditions than in the rural drinking network, mainly due to improper disinfection practices. The results show that the highest water quality was recorded at the SEEU (DWQI = 92.69), whereas the lowest quality at Shipkovica (DWQI = 63.18). Conclusion: This study strongly recommends the immediate correction of these

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.072
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9280.870

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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicFecal contamination and water qualityFrench-language works237,207