Bibliographic record
Abstract
What is the nature of the field? What is the nature of the electromagnetic field or gravity field? Is it possible that a field would be the smallest particle that we have not yet been able to reach, or is it not possible? Would it be tiny particles defusing out of photons (perpendicularly), producing Electric fields (E) and Magnetic fields (M), while a gravity field keeps these tiny particles connected to that photon?These questions are related to the following hypothesis of the Electro-Magnetic-Gravity (EMG) field that we perform testing for. We investigate if E, M, G, EM, and EMG Fields are made of tiny particles named the Field Particle (FiPa). The research is divided into sections. In one section, we explore the EM-Field morphology and its FiPa and whether it defuses out of photons. In another section, we research whether each field has its own FiPa or if there is only one type of FiPa for all fields. In another section, I dedicate the research to investigating the Gravity Field tiny Particles (GFiPa) and whether it keeps the connection between EM-Field tiny Particles (EM-FiPa) and the Photon. For this research paper, we focus on investigating the existence of Field Particles (FiPa). Therefore, we start by exploring one of the fields, the Magnetic Field, to discover its FiPa if it exists.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".