The Association of Lunar Phases on Calving in Montbéliarde Dairy Cows in the Franche-Comté Region, France
Bibliographic record
Abstract
The Moon is at the centre of many popular beliefs including that the number of births increases during Full Moon days, followed by many breeders to anticipate calving periods. However, it has been rarely explored in dairy cattle farming. This retrospective study was conducted to evaluate the association of lunar cycles on calving distribution, with particular focus on a potential increase during full-moon nights. Data from 383,926 calvings of Montbéliard breed that occurred between March 2022, and January 2025, mostly in Franche-Comté (98.2%), France were analyzed. Statistical analysis was performed using the Generalized Linear Mixed Model (GLMM). Results revealed significant association of the lunar cycle on calving distribution, it was observed a higher calving probability than the average (p < 0.001, +15%) during the New Moon, and a lower calving probability than the average during the First Quarter and Full Moon phases (p < 0.001 for both and -1.5% and -11%, respectively) in all groups, primiparous, multiparous, male and female. The observed patterns may have practical implications for veterinarians and breeders, particularly in ensuring adequate colostrum intake, thereby supporting improved management of parturition periods.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".