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Record W2265363206 · doi:10.13031/aim.20131619771

Survey on foaming deep-pit swine manure

2013· article· en· W2265363206 on OpenAlexaboutno aff
Neslihan Akdeniz, Larry D. Jacobson, C. J. Clanton, Brian P. Hetchler

Bibliographic record

Venue2013 Kansas City, Missouri, July 21 - July 24, 2013 · 2013
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsnot available
FundersIowa State University
KeywordsFoaming agentManureEnvironmental scienceWaste managementAnimal scienceAgricultural scienceMaterials scienceAgronomyComposite materialBiologyEngineeringPorosity

Abstract

fetched live from OpenAlex

<abstract> <bold>Abstract.</bold> Foaming on manure surfaces in deep-pit barns is not a completely new challenge, but starting in 2009 foaming incidents significantly increased. In the past five years, 30 to 40 flash fires and/or explosions, believed to be related to the presence of foaming in deep-pits, have been reported in the Midwest U.S. and Canada. In this study, a survey (electronic and hard copy) was developed and distributed to swine producers throughout the Midwest to document the prevalence of foaming on swine farms with deep-pits and determine if any correlations exist between foam formation and facilities and management practices. The survey results were collected from September 2012 to May 2013. Total of 225 producers (80.0% IA, 8.9% IL, 4.9% MO, 3.1% MN, 2.2% MI, 0.9% IN) responded to the survey. There were 1388 rooms (65.5% grow-finish and 34.5% wean-to-finish) and 1334 deep-pits. Foam was present in 322 pits out of 1,334 pits (24.1%). Out of 225 producers, 132 producers (58.7%) had at least one foaming pit. Total of 13 producers, 9.8% of the producers who had at least one foaming pit, had an explosion or a flash fire. Foam was a concern mainly in summer and fall. Only 37% of the producers checked their pits frequently (once a week). Solids content of the manure and unpleasant smell in drinking water were found to be significantly correlated with the presence of foam.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.012

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 head0.026
GPT teacher head0.240
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2013
Admission routes1
Has abstractyes

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