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Suitability assessment of a volcanic endorheic lake for aquaculture

2024· article· en· W4400359615 on OpenAlexaboutno aff
H A Rustini, Asep Sapei, Etty Riani, Astried Sunaryani, Arianto Budi Santoso, Sulung Nomosatryo, Fajar Setiawan, A Rahmadya

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAquacultureWater qualityEnvironmental scienceNitrateTotal dissolved solidsEnvironmental engineeringFisheryFish <Actinopterygii>EcologyBiology

Abstract

fetched live from OpenAlex

Abstract Lake Batur, a volcanic endorheic lake, has been utilized for aquaculture. In 2013, the regional authorities of Bangli Regency designated the Lake Batur area as a Minapolitan, allocating it for aquaculture development within a specified limit of 5% of the lake’s surface. However, a mere five years post-designation, research emerged revealing the lake’s incapacity to sustain aquaculture operations exceeding 1% of its area. This study delves into an assessment of Lake Batur’s suitability for aquaculture, utilizing pre-regulation water quality data and employing the Canadian Council of Ministers of Environment (CCME) Water Quality Index (WQI). Key water quality parameters, including pH, dissolved oxygen, unionized ammonia, nitrite-nitrogen, nitrate-nitrogen, orthophosphate, total nitrogen, total phosphorus, and total dissolved solids, were considered. The findings unequivocally indicate that the lake’s water quality renders it unsuitable for aquaculture. Additionally, this paper examine the imminent threats posed by aquaculture development in the Lake Batur region.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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