Study of some parameters of modified Chaplygin gas in Galileon gravity theory from observational perspective
Bibliographic record
Abstract
We have assumed the Friedmann–Robertson–Walker model of the universe in Galileon gravity, which is filled with dark matter and modified Chaplygin gas (MCG) type dark energy. We present the Hubble parameter in terms of some unknown parameters and observational parameters with the redshift z. Some cosmological parameters are reconstructed and plots are generated to study the nature of the model and its viability. It is seen that the model is perfectly consistent with the present cosmic acceleration. From observed Hubble data (OHD) set or Stern data set of 12 points, we have obtained the bounds of the arbitrary parameters (A, B) and (A, C) by minimizing the χ2 test. Next because of joint analysis of OHD + baryonic acoustic oscillation (BAO) and OHD+BAO+CMB observations, we have also obtained the best fit values and the bounds of the parameters (A, B) and (A, C) by fixing some other parameters. The best-fit values and bounds of the parameters are obtained with 66%, 90%, and 99% confidence levels for OHD, OHD+BAO, and OHD+BAO+CMB joint analysis. Next we have also taken type Ia supernovae data set (union2 data set with 557 data points). The distance modulus μ(z) against redshift z for our theoretical MCG model in Galileon gravity have been tested for the best fit values of the parameters and the observed type Ia supernovae union2 data sample and from this, we have concluded that our model is in agreement with the union2 sample data.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".