Erratum to “Metabolic parameters in transition cows as indicators for early-lactation culling risk” (J. Dairy Sci. 95:3057–3063)
Bibliographic record
Abstract
In Table 1 (page 3058), the number of herds in the last column should be 49, instead of 21. The corrected table is shown below with the corrected value in bold.Table 1Data sources used in pooled analysis of metabolic risk factors for culling in early lactationVariableDuffield et al.(1998)LeBlanc et al.(2005)Dubuc et al.(2010)Chapinal et al.(2011)Cows (no.)9961,1121,6492,222Herds (no.)2520349Culling within 60 DIM (%)10.07.46.78.8Regions in which the study was conducted1CA = California; FL = Florida; GA = Georgia; MN = Minnesota; NC = North Carolina; NY = New York; ON = Ontario, Canada; SC = South Carolina; VA = Virginia; WI = Wisconsin.ONONNY, ONCA, FL, GA, MN, NC, NY, ON, SC, VA, WISample time relative to calving/metaboliteWk −1 NEFAXXX BHBAXXX CalciumXXXWk +1 NEFAXXX BHBAXXXX CalciumXXXWk +2 NEFAXX BHBAXXX CalciumXX1 CA = California; FL = Florida; GA = Georgia; MN = Minnesota; NC = North Carolina; NY = New York; ON = Ontario, Canada; SC = South Carolina; VA = Virginia; WI = Wisconsin. Open table in a new tab The authors regret the error.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.079 | 0.035 |
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".