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Record W2080350845 · doi:10.2166/wst.2013.323

Occurrence of tylosin in swine wastewater in Mexico

2013· article· en· W2080350845 on OpenAlexaff
Liliana García‐Sánchez, Marco A. Garzón‐Zúñiga, Gerardo Buelna, Gabriela Chávez, A. Noyola, Martha Avilez-Flores, Edson Baltazar Estrada‐Arriaga

Bibliographic record

VenueWater Science & Technology · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsCentre de Recherche Industrielle du Québec
Fundersnot available
KeywordsTylosinWastewaterSlurryAnimal scienceBiologyVeterinary medicineAntibioticsEnvironmental engineeringEnvironmental scienceMicrobiologyMedicine

Abstract

fetched live from OpenAlex

This study determined a tylosin concentration in swine wastewater located in a Mexican pig farm, during different stages of the pigs' growth. The detection of antibiotics in swine wastewater is complex due to its high concentration of solids. Analytical method was developed for detection of tylosin in swine wastewater and swine slurry. Average recoveries of tylosin in the liquid and solid phase were greater than 51 and 44%, respectively, with a greater total recovery of 95%. The results indicated the presence of tylosin in swine wastewater and slurry at concentrations greater than the ones reported in the literature. In grab samples of swine wastewater, the tylosin detected showed concentrations of 56, 72 and 8.6 μg L(-1), in breeding-gestation, nursery pigs, and grow-finishing area, respectively. In composite samples, the concentration of tylosin was 11.8 μg L(-1) for the breeding-gestation area and 2.4 μg L(-1) for the grow-finishing area. For slurry, the concentration of tylosin was 20.6 and 17.8 μg L(-1), for the breeding-gestation and grow-finishing area, respectively. This study presents the detection of a high concentration of tylosin in breeding-gestation and nursery pigs. Traces of tylosin in wastewater from grow-finishing stage were found although the animals were not receiving antibiotics.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.215
Teacher spread0.208 · 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 designBench or experimental
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

Citations10
Published2013
Admission routes1
Has abstractyes

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