Genetic correlation estimates between ultrasound measurements on yearling bulls and carcass measurements on finished steers.
Bibliographic record
Abstract
Carcass and growth measurements of finished crossbred steers (n = 843) and yearling ultrasound and growth measurements of purebred bulls (n = 5,654) of 11 breeds were analyzed to estimate genetic parameters. Multiple-trait restricted maximum likelihood (REML) was used to estimate heritabilities and genetic correlations between finished steer carcass measurements and yearling bull ultrasound measurements. Separate analyses were conducted to examine the effect of adjustment to three different end points: age, backfat thickness, and weight at measurement. Age-constant heritability estimates from finished steer measurements of hot carcass weight, carcass longissimus muscle area, carcass marbling score, carcass backfat, and average daily feedlot gain were 0.47, 0.45, 0.35, 0.41, and 0.30, respectively. Age-constant heritability estimates from yearling bull measurements of ultrasound longissimus muscle area, ultrasound percentage of intramuscular fat, ultrasound backfat, and average daily postweaning gain were 0.48, 0.23, 0.52, and 0.46, respectively. Similar estimates were found for backfat and weight-constant traits. Age-constant genetic correlation estimates between steer carcass longissimus muscle area and bull ultrasound longissimus muscle area, steer carcass backfat and bull ultrasound backfat, steer carcass marbling and bull ultrasound intramuscular fat, and steer average daily gain and bull average daily gain were 0.66, 0.88, 0.80, and 0.72, respectively. The strong, positive genetic correlation estimates between bull ultrasound measurements and corresponding steer carcass measurements suggest that genetic improvement for steer carcass traits can be achieved by using yearling bull ultrasound measurements as selection criteria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".