Clinical trial to determine the productivity impact of milk urea nitrogen reports
Bibliographic record
Abstract
A clinical trial was conducted to determine the perceived and actual utility of milk urea nitrogen (MUN) notification and interpretation as a tool for monitoring protein and energy imbalances in dairy cows. Based on MUN results during the summer of 2001, 50 farms with high MUN values and 30 with low values were randomly allocated to become either intervention or control farms. From January to November 2002 (the trial period), intervention included monthly notification of individual cow MUN results, interpretation of abnormal average MUN values in subgroups of cows based on parity and days-in-milk, and suggestion of possible nutritional reasons for the abnormal MUNs. Intervention farms responded to a survey regarding report utilization, subsequent feed changes and perceptions of MUN testing. Control farms received the individual cow MUN results, but no additional interpretation. No significant differences in average MUN or standardized milk production between intervention and control farms were seen during the last three months of the trial (the outcome period). However, in herds making a feed change in response to MUN notification and interpretation (71% of intervention herds), milk production increased 2.4 lb (1.1 kg)/cow per day in the month after the feed change when compared to randomly selected herds not making a feed change during the same time period. Most dairy producers receiving the MUN notification and interpretation reports felt they knew how to use MUN reports after the trial, and felt that MUN testing was at least somewhat useful as a nutritional tool.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".