Space-time Connections With Inertial Masses of Ordinary and Novel Particles and Deducing Some Limiting Velocities From Maximal Particle Velocities
Bibliographic record
Abstract
The increasing number of physical phenomena, such as the Dark Matter, as well as the difficulties to understand the enormous distances in the Universe, encourages one to formulate matter description that goes beyond the Standard Model. Here we present the description of ordinary and novel (some as Dark Matter) particles through the bicubic equation limiting velocity solutions, globally denoted as, c1, c2 and c3, (primary, secondary and tertiary). These solutions depend on the congruent parameter z = 3 √ 3mv2/2E which connect them to m, v, and E , respectively being particle mass, velocity and energy. When the bicubic equation discriminant D and z satisfy D ≤ 0, z2 ≤ 1, the limiting velocities describe ordinary particles (electron, neutrino, etc.) and when D ⪰ 0, z2 ⪰ 1 limiting velocities describe the novel (some as Dark Matter), yet to be directly observed particles. At z = 1 ordinary particles with c1, c2 and c3 (primary, secondary and tertiary) transit from, z2 ≤ 1 into novel (some as Dark Matter) patrticles, z2 ⪰ 1 with the same values at z = 1 for novel particle limiting velocities Rc1, Rc2 and c3 (primary, secondary and tertiary).The ordinary tertiary particle limiting velocity c3 and novel primary plus secondary particle limiting velocities Rc1 and Rc2 are convenient to be deduced from maximum particle velocities. The velocity of the neutrino with v = c is a good example for c3 = c,while, with the assumption that a novel particle maximum velocity is, say, v = c•, which leads to Rc1 and Rc2 = c• . Hopefully, it may turn out that also c• = c. An example of a lethargic low energy novel particle appears to be a good candidate for gravitational Dark Matter particle.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".