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Record W3088333573 · doi:10.4236/jmp.2020.119089

Several Ways to Calculate the Universal Gravitational Constant <i>G</i> Theoretically and Cubic Splines to Verify Its Measured Value

2020· article· en· W3088333573 on OpenAlexaff
C. Mercier

Bibliographic record

VenueJournal of Modern Physics · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsCégep de Baie-Comeau
Fundersnot available
KeywordsGravitational constantPhysicsGravitationHubble's lawConstant (computer programming)Value (mathematics)Physical constantUniverseCosmological constantSpace (punctuation)Theoretical physicsMathematical physicsClassical mechanicsQuantum mechanicsCosmologyMathematicsDark energyStatisticsPhilosophyComputer science

Abstract

fetched live from OpenAlex

In 1686, Newton discovered the laws of gravitation [1] and predicted the universal gravitational constant 11 3 1 2 7 10 m kg s G --- . In 1798, with a tor- sion balance, Cavendish [2] measured 11 3 1 2 6.754 10 m kg s G --- . Due to the low intensity of gravitation, it is difficult to obtain reliable results because they are disturbed by surrounding masses and environmental phenomena. Modern physics is unable to link G with other constants. However, in a 2019 article [3], with a new cosmological model, we showed that G seams related to other constants, and we obtained a theoretical value of ( ) 11 3 1 2 6.673229809 86 10 m kg s G --- . Here, we want to show that our theoretical value of G is the right one by interpreting measurements of G with the help of a new technique using cubic splines. We make the hypothesis that most G measurements are affected by an unknown systematic error which creates two main groups of data. We obtain a measured value of ( ) 11 3 1 2 6.673262 60 10 m kg s G --- . Knowing that our theoretical value of

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.246
Teacher spread0.189 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2020
Admission routes1
Has abstractyes

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