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Record W2907636317

Transport of Escherichia coli, chloride, and nitrate through disturbed and undisturbed soil columns

2000· article· en· W2907636317 on OpenAlexaboutno aff
Terrence G. Johnson, E. de Jong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsnot available
Fundersnot available
KeywordsNitrateEscherichia coliChlorideEnvironmental chemistryChemistryEnvironmental scienceGeologyHydrology (agriculture)Soil scienceGeotechnical engineeringBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Current livestock production techniques often require the surface application of large quantities of manure.In 1996 Saskatchewan had 2.8 million cattle and 0.9 million hogs, conservative estimates suggest that this number of cattle and hogs produce approximately 60 000 Mg of manure day -1 .This number is expected to be even higher today, and would certainly be much higher if other livestock such as poultry were included.The most common disposal method for this manure is application on or in the soil.The growing environmental awareness of our society, coupled with the increased number of large-scale livestock production facilities, has greatly increased concerns regarding ground water quality.These concerns are caused by the potential for nitrate and pathogenic microorganisms such as Escherichia coli (E.coli) to be leached from the soil surface into ground water.The objective of this research was to characterize the transport of E.coli and nitrate through soil.Experiments involved leaching E.coli, nitrate, chloride and potassium through disturbed soil columns under saturated and unsaturated conditions.Transport through undisturbed columns was also studied in saturated conditions.Effluent from these columns was analyzed, both chemically and microbiologically.Results of this analysis showed that E.coli can be preferentially transported through both disturbed and undisturbed soil columns.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.997

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)0.0040.000

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 head0.192
Teacher spread0.186 · 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.

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

Citations0
Published2000
Admission routes1
Has abstractyes

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