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Record W2124280772 · doi:10.1093/ps/80.10.1451

Efficacy of In-Feed Tylosin Phosphate for the Treatment of Necrotic Enteritis in Broiler Chickens

2001· article· en· W2124280772 on OpenAlexaff
John J. Brennan, Gregory Moore, S. E. Poe, Alan G. Zimmermann, G. Vessie, D. A. Barnum, Jean Wilson

Bibliographic record

VenuePoultry Science · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCoccidia and coccidiosis research
Canadian institutionsUniversity of GuelphEli Lilly (Canada)
Fundersnot available
KeywordsTylosinBroilerAnimal scienceClostridium perfringensFeed conversion ratioOutbreakVeterinary medicineDoseBiologyBody weightMedicineMicrobiologyAntibioticsPharmacologyEndocrinologyVirology

Abstract

fetched live from OpenAlex

The efficacy of tylosin phosphate for the treatment of necrotic enteritis (NE) was investigated in a floor pen study of 2,000 broiler chickens. A model in which Clostridium perfringens was administered in the feed on Days 14 to 16 was used to initiate an outbreak of NE. Treatments, allocated at the pen level in a randomized complete block design, consisted of five levels of tylosin phosphate (0, 50, 100, 200, or 300 ppm) administered in the feed on Days 15 to 22, following the identification of an outbreak of NE on Day 15. Mortality due to NE was significantly reduced (P < 0.05) for medicated birds at all dose levels of tylosin phosphate compared to unmedicated birds. Mean NE lesion scores on Day 17 were significantly reduced (P < 0.05) by all levels of tylosin treatment compared to those of unmedicated birds, decreasing linearly from 2.66 at 0 ppm to 0.38 at 100 ppm and 0 at higher doses. Tylosin at all levels provided improvement in Day 29 body weight, average daily gain, feed to gain ratio, and average daily feed intake compared to unmedicated birds. The results of this study provide evidence that tylosin phosphate, when administered in feed, is effective in the treatment of clinical outbreaks of NE in broiler chickens and suggest that the optimal dose for this purpose is 100 ppm.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.286
Teacher spread0.253 · 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

Citations58
Published2001
Admission routes1
Has abstractyes

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