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Record W4309668626 · doi:10.1177/11786302221137437

Proximity of Water Wells to Public Water Testing Facilities in Alberta Using Drive Times

2022· article· en· W4309668626 on OpenAlexaffabout
Abraham Munene, David C. Hall

Bibliographic record

VenueEnvironmental Health Insights · 2022
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsSample (material)Environmental scienceWater utilityStewardship (theology)Water wellGroundwaterWater supplyEngineeringEnvironmental engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Approximately 10% of Albertans rely on well water for domestic purposes. The responsibility of water testing and stewardship is left to private well owners. Few well water owners conduct routine testing of their well water supplies. Drive times to public water testing facilities may be an important factor limiting a well owner's ability to conduct routine water testing. The objective of this study is to describe the proximity of water wells, using drive times, to public water testing facilities and describe the availability of facilities based on hours of operation. Using network analysis, we determined the proportion of a sample of wells within 3 estimated drive times of public water testing facilities. 5872 wells were included in the sample. One hundred and seven water testing facilities were mapped within the province. Of the 5872 wells mapped, 89% were located within 30 minutes of a water testing facility, 15% were located within 0 to 10 minutes of a water testing facility, 48% were located between 10 and 20 minutes of a water testing facility and 37% were located within 20 to 30 minutes of a water testing facility. Further analysis revealed that access to water testing facilities may be influenced by the hours of operation of the facilities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.200
Teacher spread0.179 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2022
Admission routes2
Has abstractyes

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