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Record W4392976391 · doi:10.4006/0836-1398-37.1.31

New gravitational model and quantization formula of the gravitational constant

2024· article· en· W4392976391 on OpenAlexvenueno aff
Ning Kang

Bibliographic record

VenuePhysics Essays · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsGravitational constantGravitationQuantization (signal processing)Constant (computer programming)Classical mechanicsAlgorithmMathematics

Abstract

fetched live from OpenAlex

The existing theories of gravitation cannot solve the problem of the gravitational quantization, and the exact value of the Newtonian constant of gravitation G has not been determined. Therefore, the essence of gravity needs to be deeply explored. Here, we show that a new gravitational model is proposed, which is of the viewpoint that the universe is a composition of elementary particles and gravitational lines, and the elementary particles are connected by gravitational lines, and the essence of gravity can be tension of the gravitational lines. Based on Newton's law of gravitation, quantum mechanics, and simple harmonic wave equation, the dynamic model of gravitational driven photons is constructed: G m g 2 / l p = Δ n ⋅ h c / λ . The quantization formula of the gravitational constant is derived: G q = K h 3 / 2 π c 2 m g 4 . The calculated average is G = 6.678 804 09 × 10−11 m3 kg−1 s−2. Compared with the recommendations value of the CODATA in 2018, the deviation obtained is 0.067%. The quantum formula of gravity is derived: f G = K h 3 / 2 π c 2 m g 2 . The gravitational model proposed in this paper solves the problem of gravitation quantization, deduces the formula of the gravitational constant and gravitational quantum, and provides a new theoretical method for deeply revealing the essence of gravity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.013
GPT teacher head0.265
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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