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Rapid microbial methods can improve public health protection

2010· article· en· W2271319420 on OpenAlexaboutno aff
Martin J. Allen, Pierre Payment, Jennifer L. Clancy

Bibliographic record

VenueAmerican Water Works Association · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsnot available
FundersDrinking Water InspectorateU.S. Environmental Protection Agency
KeywordsCertificationPublic healthCompliance (psychology)BusinessChromogenicTurnaround timeEnvironmental healthRisk analysis (engineering)MedicineOperations managementEngineeringNursingPolitical scienceChemistry

Abstract

fetched live from OpenAlex

Regulatory, political, and institutional barriers have prevented broader use of rapid, simple, and inexpensive microbiological tests for Escherichia coli. By permitting greater use of chromogenic microbiological methods for compliance requirements by trained and certified operators of smaller public water systems, the cost of compliance should remain the same or decrease than when using distant laboratories. In fact, the lower cost of such methods would allow more frequent testing. New microbial methods allow greater public health protection because they are more sensitive to smaller amounts of contaminants in addition to allowing faster turnaround times, which would allow faster notification to the public. This article describes the current status of chromogenic enzyme tests; the experiences of Alaska and some Canadian provinces/territories in their onsite use, especially for facilities serving remote areas; and, the barriers that must be addressed before they can be broadly adopted for treatment performance or compliance monitoring.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0010.000

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 head0.019
GPT teacher head0.284
Teacher spread0.265 · 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 designOther design
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

Citations7
Published2010
Admission routes1
Has abstractyes

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