Dynamic Universe Model Explains the Variations of Gravitational Deflection Observations of Very-Long-Baseline Interferometry
Bibliographic record
Abstract
This paper explains the reasons behind the wide range of values of gravitational deflection (bending) results of Very Long Baseline Interferometry (VLBI) observations, using SITA calculations of Dynamic Universe Model. These higher ranges in VLBI results are beyond explainable values of general relativistic predictions as well as with parameterized post-Newtonian (PPN) formalism, even after accounting for the standard errors. Dynamic Universe model’s built in capabilities of considering simultaneous and dynamic gravitational effect of Sun, planets, local stars etc., makes these discrepancies comprehendible. For doing so, the abilities of Dynamic Universe Model are extended into micro world i.e., the masses of light photons and radio wavelength photons, Neutrinos, electrons and protons etc., by extending from the original mathematical formulation for Dynamic Universe model viz., for planets, stars, Galaxies etc. Later 76 theoretical experiments on grazing radio photons were conducted with different initial xyz coordinates in different directions and with the same status of solar system as on 01.01.2000@00.00:00 hrs, for all these experiments. The resulting bending angles of all these experiments were plotted in a graph against solar elongation angle, which confirms that ‘gravitation of all planets etc.,’ is to be considered as suggested by many researchers for explaining the discrepancies of VLBI observations. This work is a theoretical and computational work and the overall combined results as shown are consolidated in this paper.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".