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Record W4296620545 · doi:10.1093/jas/skac247.131

155 Effect of Forage Inclusion Strategy on Finishing Beef Cattle Performance and Liver Abscesses

2022· article· en· W4296620545 on OpenAlexaff
Tyen J Paterson, G.B. Penner, Bart Lardner, Emma C. Stephens, Robert J. Gruninger, Wenzhu Yang, K. A. Beauchemin, Tim A. McAllister, Gabriel O Ribeiro

Bibliographic record

VenueJournal of Animal Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsTylosinForageAnimal scienceMarbled meatBeef cattleCarcass weightBody weightBiologyVeterinary medicineMedicineAgronomyAntibioticsBiochemistryEndocrinology

Abstract

fetched live from OpenAlex

Abstract This study evaluated different strategies of forage inclusion for finishing beef cattle and their impact on performance, carcass quality, and liver abscesses. Steers (n=360, 400±29 kg) were blocked by weight and randomly assigned to one of four treatments (15 steers/pen, 6 pens/treatment) in a complete randomized experiment. Treatments were: 1) positive control (+CON) fed a diet (7.5% forage on a diet DM basis) with tylosin (11 mg/kg); 2) negative control (–CON; control diet without tylosin); 3) a diet where forage concentration decreased (DECR) every 42 d and was static for the last 84 d (forage represented 15%, 9%, 3%, and 3% of DM, respectively) without tylosin; and 4) a diet where forage concentration increased (INCR), the inverse of the DECR without tylosin. There were no differences in initial BW, DMI, and G:F (P≥0.38). The INCR steers had lower ADG (1.63 vs. 1.74 kg, P=0.05), total BW gain (287 vs. 306 kg, P=0.05), and tended to have lower final BW and carcass weight (P=0.07) compared to +CON, with no differences from the other treatments. No differences were observed for carcass dressing percentage, ribeye area, marbling scores, and quality grades (P≥0.41). Backfat thickness and yield score were lower for INCR steers (14.2 mm and 3.42) compared to –CON (16.9 mm and 3.82, P=0.04), while other treatments did not differ. There was no difference for the percentage of steers with liver abscess or severe abscess (A+; P≥0.17). However, the percentage of steers with minor liver abscesses (A) was numerically less for +CON (51.8%) and DECR (51.8%) compared to –CON (62.2%) and INCR (64.3%, P=0.055). This suggests that higher dietary concentrations of forage in the beginning stages of finishing, with a subsequent decline thereafter has the potential to decrease the proportion of minor liver abscesses, similar to the inclusion of tylosin in a high-grain diet, without impacting growth performance or carcass quality.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.254
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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