Publication2025
Machine Learning-Enhanced Monitoring and Assessment of Urban Drinking Water Quality in North Bhubaneswar, Odisha, India
The record
- Type
- Publication
- Date
- 1 September 2025
- Level
- International — held abroad
- Journal
- Limnological Review
- Volume
- 25
- Issue
- 3
- Published
- 1 September 2025
- DOI
- 10.3390/limnolrev25030044
- Scopus ID
- 105017435633
- ISSN
- 16425952
- Authors
- 7
- Open access
- Yes
- Citations
- 3
- International co-authorship
- Yes
- Co-author countries
- HR, IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
6 Ensure availability and sustainable management of water and sanitation for all
Machine learning models (Decision Tree 91.7%, Random Forest 92.7% accuracy) for drinking water quality assessment in North Bhubaneswar integrating WQI, geospatial analysis supports sustainable access to clean water.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
11 Make cities and human settlements inclusive, safe, resilient and sustainable
Urban water quality monitoring contributes to sustainable city infrastructure and public health protection.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Clean drinking water access through quality monitoring directly supports health and well-being in urban populations.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
Evidence
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Machine Learning-Enhanced Monitoring and Assessment of Urban Drinking Water Quality in North Bhubaneswar, Odisha, India”. Kortex.