Effect of Lunar Cycle on Delivery Rates in a Tertiary Care Hospital in India - A Retrospective Study
Bibliographic record
Abstract
BACKGROUND From ancient period, moon has been held responsible for many biological activities. The lunar cycle has long been thought to have many chemical & physical effects on human beings especially women. The menstrual cycle, conception, delivery and even fertility have been closely linked to the moon’s cycles. The relation of lunar phases to the birth rate has been the focus of considerable research with still controversial results. We wanted to study the moon phases with regard to birth rate, relationship between lunar position and the time of delivery, preterm delivery, intrauterine fetal death (IUFD), instrumental delivery, normal vaginal delivery (NVD), lower segment Caesarean section (LSCS) and multiple pregnancy. METHODS Retrospective data from daily antenatal mother admissions, and delivery rates present in the public domain of a tertiary care hospital of Midnapore Medical College, Midnapore, India from 1st Oct 2019 to 30th Sept 2020 was evaluated with one-way analysis of variance (ANOVA). RESULTS Delivery rates were not related to lunar 1 st quarter, full moon, new moon, and last quarter of lunar cycle with total delivery (P < 0.05), LSCS (P > 0.05), NVD (P > 0.05), instrumental delivery (P > 0.05), twin delivery (P > 0.05), and IUFD (P > 0.05). CONCLUSIONS Birth rates do not correlate with phases of the moon. KEYWORDS Lunar Cycle, Birth, Delivery, Pregnancy, Obstetrics
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".