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Record W4390888419 · doi:10.32672/jse.v9i1.714

Penentuan Status Mutu Air Sungai Wrati Pasuruan Jawa Timur dengan Indeks Kualitas Air

2023· article· en· W4390888419 on OpenAlexaff
Abdillah Akmal Karami, Harmin Sulistiyaning Titah

Bibliographic record

VenueJurnal Serambi Engineering · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsEnvironmental scienceWater qualityPollutionWater resource managementHydrology (agriculture)PollutantRiver pollutionEnvironmental engineeringEngineering

Abstract

fetched live from OpenAlex

The Wrati River is located in Pasuruan Regency. This river crosses three sub-districts and six sub-districts, with a total distance of 13.6 kilometers. The subdistrict through which this river passes has land use for household, agricultural, and industrial purposes. These activities hurt rivers, causing pollution and decreasing water quality. Determining water quality status is very important to understand the suitability of river water for various purposes. Understanding water quality can be fundamental information for managing and preventing river pollution. The pollutant index approach used in this research refers to the guidelines in the Decree of the Minister of the Environment Number 115 of 2003. The research results show that the water quality of the Wrati River from upstream to downstream is included in the lightly polluted category at each sampling point, with an index value of 4.94. The main factor causing light pollution in Wrati River water is the excessive phosphate content and other parameters that exceed the specified quality standards. Based on the findings of this research, waste management efforts need to be made to improve the quality of this river water.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.203
Teacher spread0.196 · 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.

Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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