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Record W1981634999 · doi:10.1080/15287390490492421

BACTERIAL PATHOGENS IN RURAL WATER SUPPLIES IN SOUTHERN ALBERTA, CANADA

2004· article· en· W1981634999 on OpenAlexaffabout
Victor P. J. Gannon, T. Graham, Susan Read, Kim Ziebell, Ann Muckle, Julie Y. Mori, James Thomas, L. Brent Selinger, Ivan Townshend, James Byrne

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsUniversity of LethbridgeHealth Canada
Fundersnot available
KeywordsSalmonellaRaw waterSampling (signal processing)Veterinary medicineAgricultureSerotypeGeographyPathogenIrrigationBiologyEnvironmental scienceMicrobiologyEcologyBacteriaEnvironmental engineeringArchaeologyMedicine

Abstract

fetched live from OpenAlex

Raw river and irrigation water in the Oldman River Basin in southern Alberta was tested for the presence of two bacterial pathogens, Escherichia coli O157:H7 and Salmonella spp., over the last 2 yr (2000-2001). The number of E. coli O157:H7 and Salmonella spp. isolated from raw water peaked during the summer months. While E. coli O157:H7 was only isolated from 11/802 (1.35%) of raw water samples over the entire sampling season in 2000 and from 16/806 (2.05%) of the samples in 2001, the pathogen was isolated one or more times from 10/35 (28.55%) sampling sites in 2000 and from 13/40 (32.55%) sampling sites in 2001. Salmonella was isolated from 44/802 (5.55%) of raw water samples in 2000 and from 122/822 (14.95%) of the samples in 2001; the pathogen was isolated one or more times from 25/35 (71.45%) sampling sites in 2000 and from 29/40 (72.55%) sampling sites in 2001. Certain sites had multiple pathogen isolations in the same year and from year to year. Salmonella Rublislaw was the most common Salmonella serovar isolated in both years, accounting for 52.45% of isolates.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.943

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 head0.005
GPT teacher head0.229
Teacher spread0.224 · 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 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

Citations57
Published2004
Admission routes2
Has abstractyes

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