Behavioral changes to detect estrus using ear-sensor accelerometer compared to in-line milk progesterone in a commercial dairy herd
Bibliographic record
Abstract
The first objective of this study was to compare behavioral and ear temperature changes using accelerometer ear tags (CowManager system; Sensor) during the declining progesterone (P 4 ) phase (expected estrus) and the luteal phase determined using in-line milk P 4 analysis (Herd Navigator system; HNS). The second objective was to evaluate the accuracy of each Sensor metric to detect estrus compared to HNS in a commercial dairy herd. Forty-six cows (23 young [1 to 2 lactations] and 23 mature [3 to 6 lactations]) at 20 days in milk (DIM) were fitted with Sensor tags, and P 4 profiles measured via HNS until 90 DIM. Sensor metrics analyzed were Resting, Ruminating, Eating, Active, High-Active, and ear temperature (Etemp). The day of milk P 4 decline below the 5 ng/mL threshold in the HNS was designated as d -1 (LSM ± SEM; 3.42 ± 0.08 ng/mL) and the day of expected estrus as d 0. Significant increases (LSM ± SEM) were observed at d 0 in Active (5.01 ± 0.14 min/h) and High-Active (8.70 ± 0.25 min/h) behavior responses as well as in Etemp (29.45 ± 0.08°C) compared with the luteal phase (Active: 4.46 ± 0.13 min/h; High-Active: 6.40 ± 0.22 min/h and Etemp: 28.69 ± 0.08°C). The greatest estrus detection accuracy (Youden Index [J: performance]) single metric was achieved using Etemp (0.24 J) followed by Resting (0.20 J) and High-Active (0.17 J) in all cows. Greater accuracy was observed in Young cows (Etemp: 0.44 J; Resting: 0.33 J; and High-Active: 0.25 J) than in Mature cows (Etemp: 0.09 J; Resting: 0.12 J; and High-Active: 0.13 J). Similarly, accuracy was greater when only healthy cows (cows with no postpartum health events) were compared (Etemp: 0.33 J; Resting: 0.31 J; High-Active: 0.20 J) to unhealthy cows (Etemp: 0.11 J; Resting: 0.02 J; High-Active: 0.02 J). The combination of behavior and Etemp metrics optimized the estrus detection accuracy in all the cows (0.30 J), Young (0.46 J), Mature (0.26 J), Healthy (0.45 J), and Unhealthy (0.11 J) cows compared to a single metric approach. Age and postpartum health affected the estrus detection accuracy using Sensor tags.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 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".