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Record W4205201573 · doi:10.4006/0836-1398-34.4.591

A new understanding of the origin of electric current

2021· article· en· W4205201573 on OpenAlexvenueno aff
Wei Fan

Bibliographic record

VenuePhysics Essays · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)PhysicsMomentum (technical analysis)Current (fluid)ElectricityElectric currentVoltageTheoretical physicsQuantum mechanicsComputer scienceEconomicsThermodynamics

Abstract

fetched live from OpenAlex

Because charge, current, resistance, and voltage are understood based on the perspective of electricity, they can describe various electrical phenomena well, but they cannot explain their origins. Therefore, this article attempts to propose a new understanding of these phenomena from the perspective of mechanics to obtain a feasible way of explaining their origin and to solve problems that cannot be explained from the perspective of electricity. Specifically, this paper attempts to explain the origin of electric charge to obtain a new understanding of the origin of current and to obtain a new understanding of voltage and resistance by explaining the origin of current. Finally, from the perspective of mechanics, the origin of charge can be understood as a manifestation of electron momentum, the origin of current can be understood as a momentum flow, the origin of resistance can be understood as a momentum resistance, and the origin of voltage can be understood as a potential pressure (potential difference) of electron orbital potential. This new understanding of the origin of current from a mechanical perspective can provide a new theoretical explanation for high-temperature superconductivity.

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)0.003
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.009
Scholarly communication0.0040.015
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.286
Teacher spread0.253 · 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
Published2021
Admission routes1
Has abstractyes

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