PSI-4 Effect of rumen protected capsaicin on dry matter intake, average daily gain, and carcass characteristics in finishing beef cattle
Bibliographic record
Abstract
Abstract The objective was to evaluate growth performance and carcass characteristics for feedlot cattle fed two sources of rumen protected capsaicin at two dose rates. A total of 450 steers, stratified by BW, were assigned into 30 pens. Pens were randomly assigned to receive 1 of 5 treatments containing (DM basis) of 86.2% barley grain, 6.0% barley silage, 6.2% canola meal, and 1.6% vitamin and mineral supplement. Treatments contained no additive (CON) or included a low or high dose of Nexulin (100 mg/d for NEXLO and 330 mg/d for NEXHI) or CapsXL (77 mg/d CAPLO or 250 mg/d for CAPHI). Steers averaged 507 kg BW at the start of the study and 686 kg at the end of the study (69 days on feed) with no differences among treatments (P > 0.28). Dry matter intake, ADG, gain:feed, dressing percentage, backfat thickness, and rib-eye area were not affected by treatment (P > 0.33). Steers fed CAPLO and NEXLO tended (P = 0.07) to have lesser marbling scores than CON, CAPHI and NEXHI. The proportion of steers in Canadian yield grades 1 and 2 did not differ among treatments, while those in yield grade 3 were greater (P = 0.03) in NEXLO (29%) than the CON (10.0%) and NEXHI (12.2%) treatments, with those fed CAPLO (20%) and CAPHI (19%) being intermediate but not different. Treatment did not affect the proportion of steers in quality grades B4, A, or prime, but tended to increase the proportion of steers grading AAA (P = 0.08) and decrease the proportion grading AA (P = 0.06). Overall, the data from this experiment suggest the potential for capsaicin to affect carcass yield grade, marbling score and quality grades without affecting DMI, ADG, or dressing percentage.
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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".