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Record W2143855497 · doi:10.5539/apr.v2n1p46

Variation in Mass of Entities in Condensed Media

2010· article· en· W2143855497 on OpenAlexvenueno aff
Volodymyr Krasnoholovets

Bibliographic record

VenueApplied Physics Research · 2010
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsAbsorption (acoustics)Variation (astronomy)CondensationInertiaField (mathematics)Cluster (spacecraft)Chemical physicsPhysicsPhase spaceSpace (punctuation)Atomic physicsClassical mechanicsThermodynamicsOpticsAstrophysicsComputer science

Abstract

fetched live from OpenAlex

The present paper further develops some previous results associated with the variation in mass of a systemstarting from first sub microscopic principles and the constitution of real space. The wave function ?determined in a phase space is treated as an image of the original field of inertia determined in the real space,which is generated by the moving particle. Carriers of this field, inertons, are responsible for the exchange ofmass between the substance's entities (atoms or molecules that move or vibrate in the substance). Theoverlapping of inerton clouds results in the emission and re-absorption of inertons by vibrating entities. Thus themass of atoms in a substance is not a stationary parameter, but dynamic. Methods of submicroscopic mechanicsallow a detailed study of a mass dynamics in the substance in question. Moreover, the inerton field can beexcited in a substance and can affect other substances inducing new effects, such as ‘freezing’ and clusterizationof entities, which can give rise to new chemicals. Besides, those are inertons that synchronize the coherentmotion of ultracool atoms bringing them to the cluster state, which is identified with the phenomenon ofBose-Einstein condensation.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.320
Teacher spread0.281 · 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 designBench or experimental
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

Citations10
Published2010
Admission routes1
Has abstractyes

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