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Record W2146954318 · doi:10.2136/sssaj2004.0367

Culturable <i>Escherichia coli</i> in Soil Mixed with Two Types of Manure

2006· article· en· W2146954318 on OpenAlexaff
Adrian Unc, M. J. Goss

Bibliographic record

VenueSoil Science Society of America Journal · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsUniversity of GuelphUniversity of Ottawa
Fundersnot available
KeywordsManureLoamSoil waterAgronomyManure managementLiquid manureEnvironmental scienceSoil typeChemistryBiologySoil science

Abstract

fetched live from OpenAlex

We evaluated the impact of the manure type used in soil–manure mixtures on the detection of culturable E. coli as tested in water quality monitoring. A series of incubation experiments, lasting up to 200 d, allowed evaluation of the potential impact of manure × soil interactions on the augmentation of culturable E. coli Two soil types (sandy loam and a silt loam), two manure types (liquid swine manure and solid beef cattle manure), and three temperature levels (4, 12, and 20°C) were investigated. The significance of the presence of competing microorganisms was estimated by comparing results from manure mixtures with sterile and nonsterile soils. Water content in the soil–manure mixtures was maintained close to field capacity to eliminate the specific impact of water availability. We found that culturability of the indicator organism, E. coli , changed with time and was dependent on the type of manure used and its interaction with soil. Escherichia coli could be cultured for a longer time from soils with liquid manure additions. Whereas E. coli numbers were initially higher from soils treated with solid beef cattle manure, their numbers decreased more rapidly and the duration of their apparent survival was shorter. Resilience of culturable E. coli was independent of their initial numbers in manure.

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)0.001
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 score0.572
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.007
GPT teacher head0.230
Teacher spread0.222 · 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

Citations35
Published2006
Admission routes1
Has abstractyes

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