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Record W2558043716 · doi:10.5539/apr.v8n6p86

Formation of Elements and Compounds in Space in Early Universe

2016· article· en· W2558043716 on OpenAlexvenueno aff
Abdul L. Bhuiyan

Bibliographic record

VenueApplied Physics Research · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarth Systems and Cosmic Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsPhotonElectronQuarkPositronSpacetimeUniverseVirtual particleAtomic physicsParticle physicsAstrophysicsQuantum mechanics

Abstract

fetched live from OpenAlex

At the end of the period of contraction of the universe, all objects transform into gravity particles such as photons and electron- positron pairs which exist in virtual state in spacetime at an extremely high temperature. These particles move with extremely high speed comparable to the speed of light. As the early universe starts cooling, the speed of the particles starts to decrease when photons and electron- positron pairs move out of spacetime and appear as real particles. As the temperature continues to fall due to cooling, the electron- positron pairs start forming quarks (u and d) while simultaneously the energy of photons transform into dark matter. The u quarks and d quarks then continue to form nuclei of different elements including radio elements. Simultaneously, the lighter elements such as hydrogen, nitrogen, carbon, oxygen, phosphorus, etc. form the precursors to DNAs and RNAs of living organisms.

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)0.000
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 score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.003

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 head0.044
GPT teacher head0.278
Teacher spread0.234 · 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
Published2016
Admission routes1
Has abstractyes

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