Genetic relationship between litter size traits at birth and body measurement and production traits in purebred Duroc pigs
Bibliographic record
Abstract
Heritabilities of litter size traits at birth (total number born (TNB), number born alive (NBA), and number still born (NSB)) and their genetic correlations with body measurement (body height, body length, front width (FW), chest width (CW), hind width, chest depth, chest girth, front cannon circumference, and rear cannon circumference) and production traits (ages at the start and end of performance testing (D30 and D105), average daily gain (ADG), backfat thickness, and loin muscle area) in purebred Duroc pigs were estimated. Records of performance testing for 2,835 animals and farrowing records of 1,168 litters from 437 dams were used. Genetic parameters were estimated using single-trait and two-trait animal models. Permanent environment effect was considered for litter size traits and common litter environmental effect was considered for body measurement and production traits. The estimated heritability was 0.10 ± 0.06 for TNB, 0.16 ± 0.06 for NBA, and 0.08 ± 0.05 for NSB. Positive genetic correlation of NBA was estimated with D30, D105, and ADG (0.51, 0.11, and 0.39). The estimated genetic correlation of NBA was 0.47 ± 0.17 with FW and 0.55 ± 0.18 with CW, implying that FW and CW could be promising indicator traits for efficiently improving NBA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".