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Record W2483517028 · doi:10.1596/978-1-4648-0452-6_ch2

Sindh Province’s Priority Environmental Problems

2015· book-chapter· en· W2483517028 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueThe World Bank eBooks · 2015
Typebook-chapter
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsSanitationQuarter (Canadian coin)HygieneEnvironmental healthGeographyEnvironmental pollutionMedicineEnvironmental protection

Abstract

fetched live from OpenAlex

Reports that costs of premature deaths and illnesses caused by environmental health risks in Pakistan’s Sindh Province equal 10% of Sindh’s GDP, with more than 40,000 people dying in 2009 from environmental health risks, nearly half from inadequate household water, sanitation, and hygiene, nearly one-quarter from outdoor air pollution in urban areas, and over one-quarter from household air pollution, road traffic noise, and road traffic accidents. Children comprised about 55% of total deaths (mostly under five years of age), and adults 45%. Deaths from environmental risk factors represent 18% of all deaths, and deaths among children under five represent 30% of all under-five child mortality. Environmental health risks also cause millions of cases of illness, injuries, and children with reduced intelligence. Inadequate water supply, sanitation, and hygiene remain the most pressing environmental problem, followed by air pollution, and lead exposure. Road traffic noise and accidents have substantial costs, particularly in urban areas.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.240
Teacher spread0.213 · 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