Effect of direct-fed microbials on utilization of degradable intake protein in receiving steers
Bibliographic record
Abstract
Kenney, N. M., Vanzant, E. S., Harmon, D. L. and McLeod, K. R. 2015. Effect of direct-fed microbials on utilization of degradable intake protein in receiving steers. Can. J. Anim. Sci. 95: 93–102. One hundred ninety-two crossbred beef steers (280±25 kg) were assigned to a 5×2 factorial; degradable intake protein (DIP; 80, 90, 100, 110, 120% of requirement) with and without a direct-fed microbial (DFM) primarily containing Lactobacillus acidophilus and Enterococcus faecium (109 CFU steer−1 d−1). Dry matter intake, morbidity, and immune response were not affected (P≥0.11). The first 28 d, average daily gain (ADG) did not differ with DIP in control, but increased in a cubic fashion with DFM (DIP×DFM; P=0.05). No differences (P≥0.25) in ADG occurred from days 29 to 56; however, there was a tendency (P=0.08) for a cubic increase in ADG with increasing DIP with DFM over 56 d. The first 28 d, growth efficiency did not differ across DIP levels in control but increased linearly with DFM (DIP×DFM; P=0.05). No differences (P≥0.21) in efficiency were observed from days 29 to 56 or overall. Without DFM, fecal pH decreased between days 7 and 14; however, with DFM there was no change in pH (DFM×time; P<0.05). Performance response to DFM is dependent on DIP; however, DFM does not impact morbidity or humoral immune response.
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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 | 0.000 | 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".