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Record W2136652654 · doi:10.1002/ird.549

Assessment of water quality of a river using an indexing approach during the low‐flow season

2009· article· en· W2136652654 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIrrigation and Drainage · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)Water qualityEnvironmental scienceIrrigationEnvironmental flowStreamflowAquatic ecosystemWater resource managementGeographyDrainage basinGeologyCartographyEcologyClimatology

Abstract

fetched live from OpenAlex

Abstract The River Chenab is one of the largest rivers in Pakistan with an average annual flow of 5.29 billion cubic metres (BCM). The river traverses a total length of 576 km through a number of densely populated and industrial cities in the Punjab province of Pakistan. In the present study, a segment of 292 km was monitored for a variety of cardinal water quality constituents during the low‐flow months of 2006–07 and 2007–08. Water quality indices (WQIs) were calculated for three uses of the river water, i.e. irrigation, drinking and aquatic life, using the CWQI 1.0 model developed by the task group of the Canadian Council of Ministers of the Environment (CCME). The results revealed that the lower river reach (185–233 km) was more polluted than the upper 185 km segment. In this river reach, overall WQI ranking was poor for drinking and marginal for both irrigation and aquatic life. The WQIs for all three uses were ranked poor at the sampling station located at 233 km along the river. Copyright © 2009 John Wiley & Sons, Ltd.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.208

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 studies0.0000.000
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 head0.037
GPT teacher head0.315
Teacher spread0.278 · 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