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Record W2161321366 · doi:10.14796/jwmm.c375

The Four National Taps of Singapore: A Holistic Approach to Water Resources Management from Drainage to Drinking Water

2014· article· en· W2161321366 on OpenAlexvenueno aff
Kim Irvine, Lloyd H.C. Chua, Hans S. Eikass

Bibliographic record

VenueJournal of Water Management Modeling · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
FundersNanyang Technological University
KeywordsSurface runoffStormwaterEnvironmental scienceEnvironmental planningWater resourcesSewerageWater supplyWater resource managementDrainageEnvironmental engineeringBusiness

Abstract

fetched live from OpenAlex

Water resources in Singapore are managed following the principles of a closed loop hydrologic cycle by one agency, the Public Utility Board (PUB), which promotes its management philosophy through the Four National Taps of Singapore program. The four national taps are: water from local catchment areas; imported water (from Malaysia); reused water (known as NEWater); and desalinated water. Given the uncertainty of water imports, the remaining three national taps have become increasingly important and this paper begins with a general overview of the innovative programs implemented by PUB in support of these three taps.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.237
Teacher spread0.205 · 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 designNot applicable
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

Citations50
Published2014
Admission routes1
Has abstractyes

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