Bibliographic record
Abstract
Abstract. For effective use of manure as fertilizer, manure properties must be known. However, there is a lack of information on the quantity and nutrient contents of as-removed feedlot manure. Few studies have measured the amount of manure produced by feedlot cattle, and consequently nutrient loss between as-excreted and as-removed feedlot manure is poorly understood. In Saskatchewan, a calf fed from 386 to 590 kg (850 to 1300 lbs) in 150 days can have manure production of 13.6 kg d-1, and the manure can have nitrogen content of 7.5 kg t-1 and phosphorus content of 2.0 kg t-1. Nitrogen loss between as-excreted and as-removed manure can range between 50% and 60%, and phosphorus loss can range between 10% and 30%. The model presented in this article allows feedlot operators, nutrient management specialists, and regulatory agencies to predict the properties of manure, as long as the diet, bedding usage, and moisture content are known.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".