Evaluation of long-acting implant programs for calf-fed Holsteins
Bibliographic record
Abstract
Our objective was to evaluate the relative efficacy of 3 implant programs on performance, carcass, and health outcomes in calf-fed Holstein steers. Holstein steers (n = 14,360; initial BW: 147 ± 4.5 kg) were allocated to CS1CH (Synovex C at arrival, Synovex One Feedlot at d 101, and Synovex Choice at d 271; Zoetis Inc., Parsippany, NJ), DS1CH (Synovex One Feedlot at d 101 and Synovex Choice at d 272), or DXSCH [Revalor-XS (Merck Animal Health, Summit, NJ) at d 101 and Synovex Choice at d 273). Steers in the CS1CH and DS1CH groups had greater ADG compared with those in DXSCH. Steers in the DS1CH group also had improved G:F compared with CS1CH and DXSCH. Steers in the CS1CH and DS1CH groups had greater proportions of Choice and Prime and lesser proportions of YG 1 and 2 carcasses compared with DXSCH. Initial buller treatment rates were lower in the CS1CH and DS1CH groups compared with DXSCH. Overall mortality was not different between the experimental groups. Holstein steers implanted with a Synovex One Feedlot implant had greater G:F and improved QG distribution compared with steers given a Revalor-XS implant, when both were administered at 101 d on feed. Including a low-dose implant at arrival did not improve performance and was detrimental to feed conversion and buller rates. These results demonstrate that the payout pattern of long-acting implants affects performance, carcass characteristics, and health of Holstein steers.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".