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Record W2196559525 · doi:10.5539/apr.v8n1p16

A Bridge between Quantum Mechanics and Astronomy

2015· article· en· W2196559525 on OpenAlexvenueno aff
Anna C. M. Backerra

Bibliographic record

VenueApplied Physics Research · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRelativity and Gravitational Theory
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsEinsteinUncertainty principlePhotonMassless particleTheoretical physicsPlanck lengthQuantum mechanicsSpeed of light (cellular automaton)Constant (computer programming)UniversePlanckElementary particleGeneral relativityPlanck constantQuantumQuantum gravityPlanck scale

Abstract

fetched live from OpenAlex

Small-scale physics called quantum mechanics, is still incompatible with large-scale physics as developed by Einstein in his general relativity theory. By using twin physics, which is a dualistic way of considering the universe, and following Einstein’s later advice it is possible to create a bridge between these extremes. The formulation is carried out using complementary language in which time and space necessarily occur as two distinct qualities, although they are treated analogously. The basic item in the theory is the Heisenberg unit, which has a constant amount of potential energy, and which is supplied with mathematical attributes; by interaction with another Heisenberg unit, these attributes are transformed into physical qualities. With this theory, a photon can be described such that its velocity is constant without using the related postulate, showing how the speed of light is the link between small- and large-scale physics. The Planck constant emerges from the explanation. The photon is accompanied by a so-called anti-photon, being a charged, massless particle, traveling with the same velocity and exchanging electromagnetic energy.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.014
Scholarly communication0.0050.011
Open science0.0010.003
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0140.003

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 head0.156
GPT teacher head0.384
Teacher spread0.228 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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