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Record W2199153464 · doi:10.5864/d2015-011

Evaluating appropriate maximum holding times for private well water samples

2015· article· en· W2199153464 on OpenAlexaffvenueabout
Allison Maier, Julia Krolik, Stephanie Fan, Patricia Quintin, Danielle McGolrick, Alan Joyce, Anna Majury

Bibliographic record

VenueEnvironmental Health Review · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsSt. Lawrence CollegeQueen's UniversityPublic Health OntarioBarrie Urology Group
Fundersnot available
KeywordsEnumerationGroundwaterSignificant differenceBacterial colonySample (material)StatisticsEnvironmental scienceHydrology (agriculture)MathematicsBiologyEngineeringBacteriaChemistryChromatographyGeotechnical engineeringCombinatorics

Abstract

fetched live from OpenAlex

Privately maintained groundwater wells are often located at a great distance from laboratories, creating a barrier to bacteriological testing (a necessity for determining drinking water potability). Extending the acceptable holding time between testing and collection could potentially diminish this barrier. Using seven Escherichia coli strains isolated from private well waters, the acceptability of Ontario's current allowable sample maximum holding time (48 h) was compared with time of collection. Additionally, the acceptability of extending the holding time from 48 h to 72 h was investigated. All analyses were performed using noninferiority statistical approaches to determine if later holding times had no meaningful difference in bacterial growth (determined by colony forming unit enumeration). All strains did not statistically decrease below the acceptable 10% difference during the two time periods. However, variations in the survival rates of isolates were observed, suggesting that a risk management approach should be employed when determining maximum holding times.

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.154
GPT teacher head0.384
Teacher spread0.230 · 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 designObservational
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

Citations2
Published2015
Admission routes3
Has abstractyes

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