PSX-18 Long term implanting of finished Angus Hereford steers: examining the relationship between feed and water efficiency
Bibliographic record
Abstract
Abstract Herein, we investigate the effects of a long-term release trenbolone acetate and estradiol implant (200 mg and 40 mg respectively, Revalor-XS; Merck Animal Health; Summit, NJ) on implanted [IMP; n = 9, body weight (BW) = 473.13 kg ± 25.22] and non-implanted (NIMP; n = 9, BW = 481.13 kg ± 21.78) finished Angus Hereford steers fed a single diet three times daily (0600, 1100, 1600 h). The objectives were to identify water and feed efficiency parameters and mechanisms of IMP and NIMP steers. Parameters evaluated included daily dry matter intake (DMI), freshwater intake (FWI), average daily gain (ADG), animal water units (AWU), drinking behavior, feed conversion (FC), feed conversion ratio (FCR), water conversion (WC), water conversion ratio (WCR), residual growth rate (RGR), and Kleiber index (KI). Linear mixed models were fitted to analyze the data under assumption of a completely randomized design, and variable relationships examined through partial correlation networks and principal component analysis. Implanted animals were more feed efficient than NIMP for FC (P < 0.001; SEM = 0.00), FCR (P < 0.001; SEM = 0.29), RGR (P < 0.001; SEM = 0.0.02), and KI (P < 0.001; SEM = 0.00). When evaluating water efficiency, IMP animals had less WCR (P < 0.001; SEM = 1.54) and greater WC (P < 0.001; SEM = 0.001). No differences were observed on marbling and carcass grades, but carcass weight, final BW, and rib eye area were greater for IMP groups (P < 0.001, P < 0.001, P = 0.004, respectively). For IMP, multivariate variable contribution (values > 10) appeared to associate FWI on the first and second eigenvectors with DMI, FC, and FCR. For NIMP, FWI was associated with WC, WCR, and AWU. The FWI of Implanted animals was associated with AWU, WCR, while NIMP was associated with AWU. Feed conversion ratio and DMI had the greatest node strength for the IMP animals, whereas for NIMP, KI was the only node with strength greater than 2. Our results indicate that feed and water efficiencies may share mechanistic pathways. We present a simple metric that accurately remains relevant in evaluating water requirements for both IMP and NIMP steers as AWU. We show how relationship strength is related to gain and efficiency for IMP animals, whereas metabolic activity, potentially in relation to body composition changes, drives the variation and relationships for NIMP animals.
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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 | 0.000 | 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 | 0.000 | 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".