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Global Environment Monitoring System, Water

2012· other· en· W1896432499 on OpenAlexaff
A. H. El‐Shaarawi

Bibliographic record

VenueEncyclopedia of Environmetrics · 2012
Typeother
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsWater qualityEnvironmental planningEnvironmental resource managementEnvironmental monitoringInternational watersBusinessEnvironmental protectionPolitical scienceGeographyEnvironmental scienceEnvironmental engineeringEcology

Abstract

fetched live from OpenAlex

Abstract The Global Environment Monitoring System (GEMS) grew out of the 1972 Stockholm Conference on the Environment. At that world conference, governments requested the establishment of a global monitoring program that could determine the status and trends of key environmental issues. The GEMS/Water Program was initiated in 1976 by the United Nations Environment Program (UNEP) and the World Health Organization (WHO), with the assistance of the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the World Meteorological Organization (WMO). The program had the twin objectives of improving water quality monitoring and assessment capabilities in participating countries, and determining the status and trends of regional and global water quality.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0290.010

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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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