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Record W2171387228 · doi:10.1177/0270467605276247

Linking Health Concepts in the Assessment and Evaluation of Water Distribution Systems

2005· article· en· W2171387228 on OpenAlexaff
Bryan Karney, Yves Filion

Bibliographic record

VenueBulletin of Science Technology & Society · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Academic Research Areas
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMindsetHealth assessmentHuman systems engineeringHuman healthQuality (philosophy)Risk analysis (engineering)Distribution (mathematics)Computer scienceManagement scienceProcess managementEngineeringBusinessMedicineEnvironmental healthArtificial intelligenceMathematicsEpistemology

Abstract

fetched live from OpenAlex

The concept of health is not only a specific criterion for evaluation of water quality delivered by a distribution system but also a suitable paradigm for overall functioning of the hydraulic and structural components of the system. This article views health, despite its complexities, as the only criterion with suitable depth and breadth to allow a holistic assessment of system performance. Although many decisions relating to the planning and design of water distribution systems do implicitly consider human health, engineers and planners seldom explicitly adopt a “health mindset” overall and, thus, miss the richness and possibilities of a health framework for a wider range of system evaluations, considerations, and trade-offs. This article argues why a breakdown in a healthy system will so frequently result in stresses experienced by humans and briefly reviews the concepts of human health and system health and provides specific examples of a significant interaction between the two.

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)0.019
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.003
Science and technology studies0.0020.028
Scholarly communication0.0080.008
Open science0.0010.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.425
Teacher spread0.375 · 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 designTheoretical or conceptual
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

Citations5
Published2005
Admission routes1
Has abstractyes

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