Determination of heart rate variability as an indicator of the influence of autonomic nervous system tone in cows
Bibliographic record
Abstract
The relevance of the subject is the significance of exploring the role of the autonomic nervous system in regulating the cardiovascular system to improve the welfare of productive animals. Heart rate variability is a non-invasive research method that can be useful in exploring the health status of an animal and analysing its psychophysiological state in farm conditions. The purpose of the research – to determine the effect of the tone of autonomic nervous regulation on the cow’s body, which is reflected in changes in the sympathovagal balance. Experimental research was conducted on Ukrainian Black-and-White dairy cows. To explore the variability of heart rate, an electrocardiograph was used, followed by the determination of the main indicators according to the Baevsky method, which included the determination of mode, mode amplitude, variation range, autonomic balance index, autonomic rhythm index and stress index. Based on the results of the study, three experimental groups of animals were established: normotonics, vagotonics, and sympathotonics. Considering the results obtained, cows, depending on the influence of the tone of the autonomic nervous system, have differences in the activity of the cardiovascular system. It will result in different responses to stress, which in turn will affect their productivity. Determination of heart rate variability can be one of the indispensable indicators in analysing the health of an animal on a dairy farm. This issue is a promising area of research, especially when exploring the metabolic processes of high-yield cows to improve productivity while maintaining the physiological state of the animal
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".