Bibliographic record
Abstract
Digestive disorders account for approximately 25 to 33% of deaths in feedlot cattle and likely contribute to decreased performance and efficiency of production. A variety of nutritional, management, genetic, behavioural, and environmental factors seem to be involved in the development of metabolic disorders in feedlot cattle. Excessive production of acid in the rumen is often either the cause of or a significant contributing factor to metabolic and nutritional disorders, including acute or sub-acute (chronic) acidosis, liver abscesses, and feedlot bloat. Decreasing the percentage of highly fermentable concentrates in feedlot diets by increasing roughage level or limiting feed intake should decrease the incidence of these disorders, but this approach is usually not economically feasible. Careful feed bunk management is often thought to be important for decreasing the incidence of nutritionally related disorders, but research to support its importance is limited and conflicting. Certain feed additives like ionophores seem to be effective for decreasing the incidence of acidosis and feedlot bloat, presumably through decreased total feed intake, smaller and more frequent meals, and direct effects on the ruminal microbial population. The incidence of liver abscesses can be decreased by the feeding of various antibiotics. Polioencephalomalacia (PEM) can result from several causes, including thiamine deficiency; however, recent data suggests that overproduction of H2S in the rumen is an important cause of PEM when intakes (feed and water) of sulfur are high in feedlot cattle. Key words: Beef cattle, acidosis, bloat, liver abscesses, polioencephalomalacia
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 | 0.000 | 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 | 0.001 | 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".