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Record W1962840914 · doi:10.14796/jwmm.r225-02

An Overview of Water Quality Issues in Cambodia

2006· article· en· W1962840914 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Water Management Modeling · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsRanking (information retrieval)Human Development IndexIndex (typography)GeographyEconomic growthDevelopment economicsQuality (philosophy)Developing countryHuman development (humanity)Political scienceEnvironmental protectionSocioeconomicsBusinessEconomicsComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Cambodia is amongst the poorest countries in the world, ranking 130 of 175 countries in the 2002 Human Development Index, as reported by the United Nations (www.un.org.kh/rcsystem/). The GDP per capita in 2002 was US$275 (www.state.gov/r/pa/ei/bgn/2732pr.htm). Life expectancy for men is around 54 and for women is 59, which reflects various factors, including high infant mortality rate and low living standards. Mortality due to waterborne diseases in Cambodia is high and is a situation that could be improved through better sanitary conditions and education. Cambodia also faces challenges related to population demographics (43% of the population is aged 15 or less) and the decimation of the skilled/educated sector of society during the Khmer Rouge period of 1975 -79 (Gottesman, 2003)). Estimates of the genocide vary, but Kiernan (1999) suggested about 1.67 million people, or 21% of the population perished during this period.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.086
GPT teacher head0.367
Teacher spread0.281 · 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