Identification of 5236-Year Lunar Calendrical Data Cycle Comprising of 2702-year and 2534-year asymmetric Sub-Cycles in respect of Conjunction Based Pure Lunar Calendar
Bibliographic record
Abstract
Abstract The United Nations Periodical ’State Of World Population’, authored by United Nations Population Fund, in its April 2023 issue, has declared World Population having crossed eight (8) Billion figure on November 15, 2022. Muslims, who constitute 24.9 percent of the World Population and, who are currently standing on the threshold of breaching the two(2) Billion mark, find themselves in very embarrassing situations every now & then due to the absence of an accurate, internationally accepted and shariah-compliant pure Lunar Calendar. For Muslims, there is a highly stressed religious obligation to celebrate all Islamic events as per the Islamic Lunar Hijri Calendar dates. This Calendar, also referred to simply as ’the Hijri Calendar’, is a pure lunar calendar, bound to the phases of the moon, unlike the Jewish, the Chinese and the Hindu Luni-Solar arrangements, and the start of month is marked by the physical sighting of young waxing crescent through unaided eyes. This dependence of a pure Islamic Lunar Calendar on actual astronomical observation of a young waxing crescent makes the prediction of the length of months difficult. The prediction rules/ criteria for earliest visibility of new moon were formulated as early as 300 B.C. by the Chinese and the Babylonians, followed by some good follow-up work by the Hindus. Later on, the subject attracted the best of Muslim scientific minds throughout the peak of Islamic Sciences and culminated in the formulation of a no. of prediction rules/ generalizations. However, with the fall of the Golden Muslim Era, these evolving prediction rules were pushed to oblivion for centuries together. It is only during the last century or so, that the quest into the crescent challenge has got rejuvenated and upgradation of existing astronomical criteria for better accuracy as well as formulation of new ones is well and truly underway. This work, involving the study of Lunar Calendrical Data for almost 8 Millennia from 2700 B.H. to 5500 A.H. has established that the Conjunction-Based Pure Lunar Calendrical System operates in continuous Data Cycles of 5236 Years, with an average value of 354.36707 days per year and 29.530589 days per month. The revelations are most probably going to shape-up the formulation of an Islamic Lunar Calendar with International Applicability.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".