MétaCan
Menu
Back to cohort
Record W2057358065 · doi:10.4141/a02-093

Predicting lean meat yield in beef cattle using ultrasonic muscle depth and width measurements

2003· article· en· W2057358065 on OpenAlexfundvenueno aff
R. D. Bergen, D. H. Crews, J. J. McKinnon

Bibliographic record

VenueCanadian Journal of Animal Science · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaMinistry of Agriculture - SaskatchewanUniversity of Saskatchewan
KeywordsLongissimus dorsiRepeatabilityAnimal scienceUltrasoundLean meatChemistryMathematicsBiologyMedicineChromatography

Abstract

fetched live from OpenAlex

The value of live ultrasound longissimus dorsi depth and width measurements as predictors of estimated carcass lean meat yield of steers (CARLEAN-S) and bulls (CARLEAN-B) was studied. In trial 1, equations were developed to predict estimated lean meat yield of steers (n = 116) from carcass weight (Eq. 1) or liveweight (Eq. 2), fat depth and l. dorsi area or liveweight, fat depth and l. dorsi depth × width (Eq. 3). Equation 1 was most precise (RSD = 25.6 g kg -1 ), followed by Eq. 2 (RSD = 27.8g kg -1 ) and Eq. 3 (RSD = 30.2g kg -1 ). Equations 2 and 3 predicted CARLEAN-S with similar accuracy (SEP = 23.8 vs. 24.9 g kg -1 , respectively) and were highly correlated with each other (r = 0.89) in an independent data set (n = 118). Repeatability and accuracy of pre-slaughter l. dorsi depth and width measurements were studied in yearling bulls (trial 2; n = 191). When ultrasound measurements were expressed as a percentage of the average ultrasound measurement, repeatabilities of l. dorsi depth (SER = 6.2 to 7.8%) and width (SER = 4.2 to 6.1%) measurements were similar to fat depth and l. dorsi area measurements (SER = 17.9 and 4.5%, respectively). When ultrasound measurements were compared to the corresponding carcass measurements, l. dorsi depth (SEP = 10.3 to 13.9%) and width (SEP = 6.7 to 8.5%) measurements were as accurate as fat depth and l. dorsi area measurements (SEP = 32.9 and 8.4%, respectively). Equations were developed to predict CARLEAN-B of yearling bulls (n = 82) from liveweight, 12th rib ultrasound fat depth and either l. dorsi depth × width measurements (Eqs. 4 and 5) or two l. dorsi depth measurements (Eq. 6). All equations had similar precision (RSD = 19.4 to 19.5 g kg -1 ) and predicted CARLEAN-B similarly (SEP = 25.0, 24.6 and 26.1g kg -1 for Eqs. 4, 5 and 6, respectively) in an independent data set (n = 109). All equations were highly correlated (r ≥0.97) with an equation using ultrasound fat depth and l. dorsi area in the independent data set. Longissimus muscle depth and width measurements were as valuable as l. dorsi area for predicting carcass composition of yearling beef bulls in the present study. Key words: Ultrasound, beef cattle, carcass traits

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.254
Teacher spread0.213 · 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

Citations15
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Animal ScienceSame topicGenetic and phenotypic traits in livestockFrench-language works237,207