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Record W2219541303 · doi:10.5539/apr.v8n1p42

Dark Matter and Dark Energy as a Derivate from Cosmic Photon Radiation

2015· article· en· W2219541303 on OpenAlexvenueno aff
Guido Zbiral

Bibliographic record

VenueApplied Physics Research · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsDark matterGravitationCosmologyDark energyLarge Hadron ColliderParticle physicsAstrophysicsTheoretical physicsAstronomy

Abstract

fetched live from OpenAlex

For many decades now, intensive efforts have been undertaken by physicists and cosmologists around the world to investigate dark matter (DM), without noticeable success to date. This situation leads me to believe that one of the assumptions underlying the current doctrine in physics may well be erroneous or incomplete – since a breakthrough in this field of physics and cosmology would otherwise surely have already taken place by now. For this year (2015) and the following two years, the CERN Nuclear Research Centre has set itself the task of using the LHC (now upgraded to 13 TeV) to investigate the still completely mysterious phenomenon of dark matter. The researchers at CERN favour the assumption – shared by the majority of physicists and cosmologists – that DM consists of massive non-baryonic particles (so-called WIMPs, Weakly Interacting Massive Particles) hitherto completely unknown to us, which produce a non-baryonic, static gravitational field distributed throughout the entire cosmos. I cast doubt on the above assumption that DM is massive in nature. As this paper will show, DM can be far better (and more simply) explained in terms of a non-massive gravitational derivate of those photons consumed in the expansion of cosmic space (by performing the work of expansion), those photons thereby being transformed into static physical quantities. This gravitational derivate creates a free gravitational field (decoupled from the other forces of nature) of non-baryonic, static nature, regionally varying in intensity, and this is known as dark matter.

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)0.002
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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.031
GPT teacher head0.296
Teacher spread0.265 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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