Corrigendum to “Effects of supplementing a Saccharomyces cerevisiae fermentation product during the periparturient period on performance of dairy cows fed fresh diets differing in starch content” (J. Dairy Sci. 102:3082–3096)
Bibliographic record
Abstract
In Table 9, MUN values were incorrect. The correct values are shown in bold below.Table 9Effects of supplementation of a Saccharomyces cerevisiae fermentation product (SCFP) and carryover effects of starch content of fresh diets (ST) on DMI, BW and BCS changes, milk yield and composition during the post-fresh period (d 24 ± 3 to 44 ± 3 after calving), and the interval from calving to first ovulation postpartum1LS = low-starch fresh diets; HS = high-starch fresh diets; CON = control diet, no SCFP supplementation; SCFP = SCFP-supplemented diet.VariableLSHSSEP-valueCONSCFPCONSCFPSTSCFPST × SCFPDMI, kg/d20.719.920.619.80.470.770.100.98Initial BW,2Measured on d 23 and 24 ± 3 before morning feeding. kg5765785855889.940.330.780.94BW change, kg/d0.480.610.320.320.280.420.820.82Initial BCS2Measured on d 23 and 24 ± 3 before morning feeding.2.792.832.882.830.060.390.950.44BCS change,/21d−0.18−0.13−0.15−0.110.030.480.160.77Yield, kg/d Milk42.641.939.441.21.130.090.590.26 Fat1.561.661.601.630.050.910.210.46 CP1.211.241.181.240.030.640.230.64 Lactose1.981.951.871.960.060.340.530.28 Total solids5.165.275.055.240.130.630.260.78 3.5% FCM43.845.243.444.61.170.690.250.94 Solids-corrected milk39.640.939.340.51.040.770.220.963.5% FCM/DMI2.122.292.142.260.050.91<0.010.61Milk composition Fat, %3.74aMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.4.00abMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.4.05bMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.3.95abMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.0.100.190.410.08 CP, %2.862.952.952.960.040.150.170.27 Lactose, %4.654.634.644.650.020.920.860.63 Total solids, %12.2aMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.12.6bMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.12.6bMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.12.5bMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.0.130.090.260.08 MUN, mg/dL13.7abMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.13.9abMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.14.3aMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.13.1bMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.0.410.760.230.09 SCC, 103 cells/mL37.4aMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.88.3abMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.164bMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.55.5abMeans in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.42.80.280.500.07Apparent dietary NEL3Calculated according to Dann et al. (2000). Mcal/d40.740.839.840.81.160.710.650.68 Mcal/kg of DMI1.982.071.962.070.050.840.050.86NEL balance,4Apparent dietary NEL (Mcal/d) minus NEL required for milk output and maintenance (Mcal/d). The NEL required for milk and maintenance were calculated according to Dann et al. (2000). Mcal/d2.351.361.601.550.740.750.560.59Days to FOP5Interval from calving to first ovulation postpartum (d).23.824.628.122.72.460.630.360.21a,b Means in the same row with different superscripts differ significantly (P < 0.05) when an interaction of main treatment effect was observed.1 LS = low-starch fresh diets; HS = high-starch fresh diets; CON = control diet, no SCFP supplementation; SCFP = SCFP-supplemented diet.2 Measured on d 23 and 24 ± 3 before morning feeding.3 Calculated according to Dann et al. (2000).4 Apparent dietary NEL (Mcal/d) minus NEL required for milk output and maintenance (Mcal/d). The NEL required for milk and maintenance were calculated according to Dann et al. (2000).5 Interval from calving to first ovulation postpartum (d). Open table in a new tab The authors regret the error. Effects of supplementing a Saccharomyces cerevisiae fermentation product during the periparturient period on performance of dairy cows fed fresh diets differing in starch contentJournal of Dairy ScienceVol. 102Issue 4PreviewThe objective of this study was to evaluate the effects of supplementing a Saccharomyces cerevisiae fermentation product (SCFP; NutriTek, Diamond V, Cedar Rapids, IA) during the periparturient period (d −28 ± 3 to 44 ± 3 relative to calving) on dry matter intake (DMI), milk production, apparent total-tract nutrient digestibility, and postpartum ovarian activity of dairy cows fed fresh diets varying in starch content. From d 28 ± 3 before the expected calving date until d 44 ± 3 after calving, 117 Holstein cows were fed diets with SCFP (SCFP; n = 59) or without (control, CON; n = 58). Full-Text PDF Open Access
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.150 | 0.064 |
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".