MétaCan
Menu
Back to cohort
Record W4415013502 · doi:10.5539/apr.v17n2p80

An Analysis on the Energy Structure of Mass: A Study on the Energy Field of Mass and a Model for the Mass Composition

2025· article· en· W4415013502 on OpenAlexvenueno aff
George P. Petropoulos

Bibliographic record

VenueApplied Physics Research · 2025
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsField (mathematics)Energy (signal processing)Frame (networking)Mechanism (biology)Frame of referenceSpace (punctuation)Categorization

Abstract

fetched live from OpenAlex

Mass, fundamentally linked to energy, space and time, operates as the source of an energy field that interacts with both the surrounding environment and other masses. However, leaving from the general frame fundamental questions remain unanswered. If the analysis of the field is deepened, what is the structure of the field? How do masses interact with each other? This study investigates the structural components of the energy field related to mass, analyzing the internal movements that take part for its formation. Through the examination of the interactions between these fields, the research investigates the conditions under which masses can combine to form more complex structures providing the conditions under which masses can be combined, or not, to compose bigger and more complex forms of masses. As more complex structures are formed, this paper proposes a categorization frame. The reference to established theoretical models, aims to enhance the comprehension of mass-energy mechanism and the principles governing the synthesis of complex forms. Finally, it proposes a model for the structure of masses, describing the synthesis of the fundamental molecule of hydrogen.

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)0.000
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 score0.392
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.314
Teacher spread0.285 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueApplied Physics ResearchSame topicSpacecraft and Cryogenic TechnologiesFrench-language works237,207