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Record W3178442531 · doi:10.32672/jse.v6i3.3047

Analisis Indeks Kebutuhan Lahan dan Biaya dari Perencanaan IPAL Terpadu di Kawasan Aerocity X

2021· article· en· W3178442531 on OpenAlex
Adryan Lukman Indira, Didin Agustian Permadi, Etih Hartati

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Serambi Engineering · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsWastewaterEnvironmental scienceEnvironmental engineeringForestryGeography

Abstract

fetched live from OpenAlex

District Aerocity X in Kabupaten Majalengka is a commercial and industrial area that enhances economic growth in Provinsi Jawa Barat. The district with an area of 3,480 ha is integrated into the domestic sector. However, this area also has the potential to cause harm if the waste is not treated. Following PP No 142 Tahun 2015, each industrial area must provide an effective and efficient wastewater treatment plant (WWTP). This design plan begins with the analysis of issues on the study site . The data were obtained using the Aerocity X District Pre-Development Office study method . The method of designing effective alternatives for WWTP used the weighted ranking technique (WRT), each alternative was compared with two fundamental, technical and non-technical aspects. The purpose of this design plan is to analyze the index of land and cost requirements for WWTP. The yield of wastewater was 3.99 m3/s. The most effective land and the cost is complete mix-activated sludge. The result of installing the design plan requires an area of 9,446.5 m2/m3 of wastewater and a cost of Rp5,619.53x106/m3 of wastewater.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
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 science0.0000.001
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 head0.006
GPT teacher head0.184
Teacher spread0.179 · 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