Connecting dark matter particles with the primary, obscure and normal particles through implicit causality
Bibliographic record
Abstract
The primary, obscure and normal particles with respective limiting velocities c1, c2 and c3,solutions from bicubic equation, offer comfortable venues to tackle the newly emergent dark matter particles. Particular emphasis is given to particles with velocities of O(10-3c) ( with c the velocity of light) and whose energies are from 1eV to over 100GeV for which the congruent parameter z = 3p3mv2/2E assumes values of 10-6 and 10-7. At z = 10-6 with mc2 = 100GeV one can have E = 260GeV or with E = 1eV one can have mc2 = 0:38eV; while at z = 10-7 with mc2 = 100GeV one can have E = 2:6TeV or with E = 1eV one can have mc2 = 0:038eV. The small values of the congruent parameter z allow the limiting velocities c1, c2 and c3 as well as the resulting energy expressions be written down perturbatevly in terms of the congruent parameter z.It is shown that for mc2 = 100GeV particle in the MilkyWay Dark Matter Velocity Profile (Laha, 2016), the derived limiting velocities of primary, obscure and normal particles as dark matter particles are: c1 = 1; 7c (z = 10-7), 1:34c; 2:15c (z = 10-6); c2 = +-i1; 7c (z = 10-7), +-i1:34c; +-i2:15c (z = 10-6), and c3 = v (z = 10-7; 10-6). Perturbatively, for a very small common primary and obscure particle velocity v compared to the absolute values of their limiting velocities, one shows that the obscure particle acquires (-mv2) intrinsic negative energy with respect to the primary particle,with m being their common mass.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".