A Multiple Trait Selection Index Including Feed Efficiency
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Bibliographic record
Abstract
This study was conducted to develop a multiple trait index including residual feed intake with the objective to improve net feedlot revenue in market progeny of tested bulls. The selection objective was defined as H = v1E1 + v2E2 + v3E3, where aggregate genetic merit (H) was a linear function of daily DMI (E1, kg/d), ADG (E2, kg/d), and slaughter BW (E3, kg) of progeny. Regression of steer (n = 426) net revenue on traits in the objective yielded the vector of economic weights (v) with elements v1 = $−21.49, v2 = $183.73, and v3 = $0.27. The selection criterion was defined as I = b1X1 + b2X2 +b3X3, where index value (I) was a linear function of residual feed intake (X1, kg/d), ADG (X2, kg/d), and adjusted 365-d BW (X3, kg) phenotypes of tested bulls. Residual feed intake was defined as the difference between actual DMI (kg/d) and that predicted by phenotypic regression (R2 = 0.69, residual SD = 0.58 kg/d) of daily DMI on ADG, metabolic mid-test BW, and on-test gain in ultrasound subcutaneous fat depth and longissimus area in Angus bulls (n = 99). The matrix of genetic covariances of criterion traits with objective traits (G) was estimated from recent literature and the phenotypic matrix of (co)variances among criterion traits (P) was estimated from Angus bulls with test data. Criterion weights were obtained from the solution to b = P1Gv with elements b1 = −10.12, b2 = 24.79, and b3 = −0.09. Index values ofbulls adjusted to a mean of 100 (SD = 7.81) ranged from 80.1 to 115.7. Bull ADG, residual feed intake, and 365-d BW accounted for 38, 48, and 14% of the variance in index values, respectively. Phenotypic correlation estimates (P < 0.001) for index values with bull daily DMI, ADG, and residual feed intake were −0.22, 0.53, and −0.74, respectively. Index value tended (P < 0.13) to have a lesser but favorable association with scrotal circumference. Bulls with greater index values, therefore, consumed less DM, had greater ADG, and were more efficient; however, index value was not associated (P > 0.89) with 365-dBW.
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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 | 0.000 | 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 | 0.001 | 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 it