New elementary particle hypothesis: Yin‐Yang particles
Bibliographic record
Abstract
For centuries, we have attempted to identify the most fundamental particles that make up the universe, culminating in the Standard Model, which contains more than 60 elementary particles, including fermions and bosons. However, even though the Standard Model contains many particles, it fails to reveal the inherent connections among them, raising doubts regarding whether these particles are truly the most basic building blocks of the universe. The particles in the Standard Model are similar to the chemical elements in the periodic table. Without the discovery of more fundamental particles, such as protons, neutrons, and electrons, the underlying reason for the periodicity of elements cannot be explained. This article presents a new theory of elementary particles, namely, Yin‐Yang particles, which are more fundamental than those in the Standard Model and can explain phenomena such as gravity and electromagnetic transduction. Drawing inspiration from Taoist philosophy, which holds that the universe comprises two elements, i.e., Yin (representing darkness) and Yang (representing brightness), these names are adopted in the proposed theory, albeit with distinct interpretations. The proposed particles and their associated models aim to explain a range of physical phenomena, including light, electrons, quarks, black holes, electromagnetic waves, and electromagnetic conversions. Although purely hypothetical, this theory provides a compelling framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".