MétaCan
Menu
Back to cohort
Record W4385221041 · doi:10.3390/ani13142386

Variations in the Physical Properties and Microbial Community of Dairy Cow Manure—Implications for Testing and Efficacy of Footbathing Products

2023· article· en· W4385221041 on OpenAlexfundno aff
M. Palmer, Martin J. Garland, Linda Stewart, Sarah Helyar, N.E. O’Connell

Bibliographic record

VenueAnimals · 2023
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsManureDisinfectantDairy cattleContaminationSilagePeracetic acidFood scienceBiotechnologyAgronomyEnvironmental scienceAnimal scienceBiologyChemistryHydrogen peroxideEcology

Abstract

fetched live from OpenAlex

Footbaths containing disinfectants are used on dairy farms to reduce the spread of digital dermatitis; however, they commonly become contaminated with manure. This trial investigated the physical properties and microbial composition of dairy cow manure from two production systems and examined whether the source of manure impacted the efficacy of footbathing disinfectants. Manure was collected from eighteen dairy cows, nine housed and fed grass silage (HOUSED) and nine at pasture (PASTURE). The pH and dry matter content was determined, total DNA was extracted and the region v3-v4 of the 16s rRNA gene sequenced. The efficacy of formalin and two trial products (TP1: peracetic acid and hydrogen peroxide; TP2: chlorocresol and triamine) was evaluated when mixed with manure from the two production systems. Production system differences were found in manure dry matter content, bacterial microbiome and the efficacy of both trial footbathing products but not formalin. The properties of manure affected the results of laboratory testing and therefore have the potential to influence footbathing disinfectant efficacy when footbaths are contaminated with manure. Further research into the impact of organic contaminants on the efficacy of disinfectants could facilitate the development of improved testing programmes and disinfectant products.

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)0.001
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 score0.944
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.253
GPT teacher head0.369
Teacher spread0.116 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAnimalsSame topicAnimal Behavior and Welfare StudiesFrench-language works237,207