A comparative study of MOND and MOG theories versus the <i>κ</i>-model: an application to galaxy clusters
Bibliographic record
Abstract
Many models have been proposed to minimize the dark matter (DM) content in various astronomical objects at every scale in the Universe. The most widely known model is MOdified Newtonian dynamics (MOND). MOND was first published by Mordehai Milgrom in 1983. A second concurrent model is modified gravity, which is a covariant scalar–tensor–vector extension of general relativity. Other theories also exist but have not been broadly applied to a large list of astronomical objects. Eventually, we can also mention the Newtonian fractional-dimension gravity, a gravity theory based on spaces with fractional (i.e., non-integer) dimension. A new model, called κ-model, based on very elementary phenomenological considerations, has recently been proposed in the astrophysics field. This model shows that the presence of DM can be considerably minimized with regard to the dynamics of galaxies. The κ-model belongs to the general family of theories descended from MOND. Under this family of theories, there is no need to develop a highly uncertain DM sector of physics to explain the observations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".