354 Zinc supplementation prior to transit and transit duration effects on feedlot performance and muscle fatigue of beef steers: Part II – Feeding Behavior
Bibliographic record
Abstract
Abstract This study assessed the effects of supplemental Zn on cattle feeding behavior after varying transit duration. Angus crossbred steers (80; 265 ± 18 kg) were used in a 2 × 2 factorial design. Steers were assigned to a dietary Zn treatment (DIET) and transit duration (DUR; d 0): Zn0 (no supplemental Zn) or Zn100 (100 mg Zn/kg DM; supplemented as ZnSO4, starting d -42 relative to transit) and short duration (8H; 8 h transit; 707 km) or long duration (18H; 18 h transit; 1608 km). Steers were fed ad libitum via GrowSafe bunks (GrowSafe Systems Ltd., Airdrie, AB, Canada), and steer was experimental unit (n = 1 bunk/pen; n = 5 steers/pen). On d 0, steers were stratified to trailer compartments across diets. The 8H and 18H groups departed at 1000 and 1300 h and returned at 1800 and 0700 h to pre-transit pens, respectively. Following transit, all steers received Zn100. Utilizing GrowSafe Behavior module, a feed event was characterized as a reading with < 300 s interruption with head down (FE-HD; recorded in seconds) and count (number of HD events). Intake rate (g/s) was feed consumed per FE-HD divided by FE-HD duration. Data for the 6-d post transit were analyzed as a complete randomized design utilizing PROC MIXED of SAS 9.4 (SAS Inst. Inc., Cary, NC) with fixed effects DIET, DUR, and DAY as repeated. Pre-transit values served as a covariate. During the week prior to transit, there was a DUR effect for FE-HD average and intake rate (P ≤ 0.03) where 8H had longer FE-HD but reduced intake rate than 18H. There was also a tendency for Zn100 to consume more feed per FE pre-transit (P = 0.07). Post-transit, both average intake and FE-HD average increased with days post-transit (DAY; P ≤ 0.01). Additionally, a DIET × DUR effect was observed for FE-HD count (P = 0.01) where 100 was greater than 0 within 18H and 0 was greater than 100 in 8H. A tendency for a TRT × DAY effect was noted for FE-HD count (P = 0.07) driven by Zn0 decreasing from d 3 to 4. A DUR × DAY effect (P = 0.02) was also noted for FE-HD count where 18H was greater on d 2, 4, and 5. A DUR × DAY effect was observed for FE-HD average (P = 0.01) driven by a d 3 difference where 8H was greater than 18H. Conversely, a DUR × DAY effect was observed for intake rate (P = 0.01) where 18H was greater on d 2, 3, and 6. These data indicate both transit duration and dietary Zn concentration influenced animal behavior post-transit.
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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) | 0.001 | 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".