Integrating an automated activity monitor into an artificial insemination program and the associated risk factors affecting reproductive performance of dairy cows
Bibliographic record
Abstract
administered 2 wk apart. Treatments were (1) first insemination performed by timed AI (TAI) and (2) first insemination based upon the detection of estrus by activity monitors (ACT; Heatime, SCR Engineering, Netanya, Israel) after the presynchronization, whereas cows not inseminated by the detection of estrus were enrolled in the Ovsynch protocol. Body condition score (BCS; scale 1 to 5), hock score (scale: 1 to 4), gait score (scale: 1 to 4), and corpus luteum presence detected by ovarian ultrasonography were recorded twice during the presynchronization. On the ACT treatment, 50.5% of cows were inseminated based on detected estrus, whereas 83.2% of the cows on the TAI treatment were inseminated appropriately after the timed AI protocol. Pregnancy per AI did not differ by treatment (30.8 vs. 33.5% for ACT and TAI, respectively). Success of pregnancy was affected by parity, cyclicity, BCS, milk production, and a tendency for leg health. In addition, treatment × cyclicity and treatment × parity interactions were found to affect pregnancy success, where anovulatory cows and older cows had compromised pregnancy outcomes on the ACT treatment but not on the TAI treatment. Factors affecting pregnancy outcomes varied among farms. Hazard of pregnancy by 300 DIM was affected by farm, parity, BCS, a treatment × cyclicity interaction, and a tendency for an interaction between leg health and farm. Detection of estrus was affected by farm, parity, cyclicity, and leg health, but not BCS or milk production. Expression of estrus was compromised in anovular and older cows, and by the timing of the estrus event, but not by gait score, BCS, or milk production. Increased duration of estrus, but not intensity of estrus, improved pregnancy per AI. In conclusion, using an automated activity monitor for the detection of estrus within a Presynch-Ovsynch program resulted in similar pregnancy per AI and days open compared with a reproduction program that was strictly based on timed AI for first postpartum AI. In contrast, notable variations in reproductive outcomes were detected between farms, suggesting that the use of automated activity monitors is prone to individual farm management.
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 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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 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 teacher head, 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".