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Record W7039763978

Model Dinamik Penyediaan Air Baku Melalui Pendekatan Water Sensitive City di DAS Ciliwung Hulu (Kasus Desa Bendungan, Kecamatan Ciawi, Kabupaten Bogor)

2018· article· en· W7039763978 on OpenAlexaff

Bibliographic record

VenueUniversitas Terbuka Repository (Universitas Terbuka) · 2018
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsNucleofectionTSG101Gestational periodArticular cartilage damageDiafiltrationHyporeflexia
DOInot available

Abstract

fetched live from OpenAlex

Raw water supply in the rural area still relies on the natural resources (classical), i.e. groundwater, springs, and local water supply company (PDAM) with distribution service 10%, consequently, the village community experience vulnerability of water supply in dry season. Therefore, it is needed to provide a sustainable water supply through concern for new water paradigm with water sensitive city (WSC) approach. This research aims to design a dynamics model of development of raw water supply infrastructure with a concern for new water paradigm. The analysis uses dynamics system with Powersim version 2.5a. The simulation results reveal: (a) with business as usual scenario the raw water supply of Bendungan village is only sufficient for 10 years in the future, i.e. in 2025. The condition is very vulnerable, because the raw water supply is less than the water demand, (b) with concern for water scenario through infrastructure: retention basin, domestic wastewater treatment (DWT), and industry wastewater treatment (IWT), raw water supply increase 71% from 10 years to 48 years in 2063.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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 designSimulation or modeling
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

Citations2
Published2018
Admission routes1
Has abstractyes

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Same venueUniversitas Terbuka Repository (Universitas Terbuka)Same topicBlockchain Technology in Education and LearningFrench-language works237,207