Drinking regime evaluation with continuous ruminal monitoring boluses
Bibliographic record
Abstract
Received: 2016-07-04 | Accepted: 2016-10-27 | Available online: 2017-03-31 http://dx.doi.org/10.15414/afz.2017.20.01.01-05 The aim of this study was to continuously monitored drinking regime of 7 dairy cows of Holstein breed using boluses during 24 weeks of lactation in relation to the outside temperature and observed daily drinking regime with the impact of drinking on rumen temperature at University Experimental Farm in Oponice. Animals were fed once daily and milked 3 times per day. The bolus pH and temperature values implemented via esophagus were measured every 15 minutes (96 data points per day) with accuracy ±0.1 ph and °C. Outside temperature by FREEMETEO meteorological server (48 times per day) was measured. Outside temperature can affect the drinking regime of dairy cows. During lactation weeks with higher outside temperature higher average number of drinking events (ANDE) was determined. The biggest difference between weeks in ANDE 18.33 % (p = 0.000) was found. Daily ANDE 9.25 ±1.85 and average daily temperature (ADT) 19.03 ±5.19 °C were observed. The most of the drinking events (NDE) concentrated to 4 main peaks (25.17  %) during working hours (74.98  %) was found. After the feed intake and milking the highest frequencies of NDE were observed. The highest average ruminal temperature after drinking (ARTAD) during night before first feeding due to lower NDE in this time were found. Overall ARTAD 36.86 °C was observed. The most measured ruminal temperatures after drinking (RTAD) (51.53 %) in the interval 35â37 °C were found. This research proved that continuous ruminal monitoring with boluses is an appropriate tool for drinking regime evaluation and heat stress determination in herd of dairy cows. Keywords: dairy cows, Hostein cattle, bolus, rumen, temperature, water intake, outside temperature References Arias, R., Mader, T. and Escobar, P. (2008)  Climatic factors affecting cattle performance in dairy and beef farms. 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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".