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Record W4211056601 · doi:10.1007/978-1-59745-029-4_7

Membrane Filtration

2006· book-chapter· en· W4211056601 on OpenAlexaff
J. Paul Chen, Honghui Mou, Lawrence K. Wang, Takeshi Matsuura

Bibliographic record

VenueHumana Press eBooks · 2006
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRaw waterWater supplyBusinessConsumption (sociology)PopulationNatural resource economicsResource (disambiguation)Raw materialHuman lifeFiltration (mathematics)Environmental scienceEnvironmental engineeringEconomicsEcologyEnvironmental health

Abstract

fetched live from OpenAlex

With the rapid increase of demand in industries and daily life, water has become an increasingly valuable but scarcer resource for human being. Take Singapore as an example. Almost half of its water supply is being imported from Malaysia. The daily water consumption has risen eight times while the population has only grown three times since 1950 (1). This increase has led to a greater pressure on the use of limited raw water resources and the capacity of treatment plants. The potential shortfall between supply and consumption needs to be addressed if domestic and industrial customers are to continue enjoying uninterrupted supply

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.674
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.044
GPT teacher head0.241
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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations20
Published2006
Admission routes1
Has abstractyes

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