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Record W7017829067

Catalyzing water for sustainable Development and growth

2013· report· en· W7017829067 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2013
Typereport
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsnot available
FundersMinistry of EnvironmentYonsei UniversityGovernment of CanadaMcMaster UniversityStockholm Environment Institute
KeywordsSustainable developmentFraming (construction)SustainabilityWater developmentWater resourcesWater quality
DOInot available

Abstract

fetched live from OpenAlex

Adeel, Z., Bullock, A., Chaudry, M.A., Kuylenstierna, J., Qadir, M., Schuster-Wallace, C.J. & Weitz N. (2013). Catalyzing water for sustainable Development and growth. Framing Water Within the Post 2015 Development Agenda: Options and Considerations. United Nations University. https://collections.unu.edu/view/UNU:2656 CC BY-NC-SA 3.0 IGO

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0200.009

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 head0.008
GPT teacher head0.155
Teacher spread0.147 · 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 designBench or experimental
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

Citations0
Published2013
Admission routes1
Has abstractyes

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