Bibliographic record
Abstract
We analyse the possibility that the observed cosmological redshift may be cumulatively due to the expansion of the universe and the tired light phenomenon. Since the source of both the redshifts is the same, they both independently relate to the same proper distance of the light source. Using this approach we have developed a hybrid model combining the Einstein de Sitter model and the tired light model that yields a slightly better fit to Supernovae Ia redshift data using one parameter than the standard ΛCDM model with two parameters. We have shown that the ratio of tired light component to the Einstein de Sitter component of redshift has evolved from 2.5 in the past, corresponding to redshift 1000, to its present value of 1.5. The hybrid model yields Hubble constant H0 =69.11(±0.53)km·s-1 ·Mpc-1 and the deceleration parameter q0 =-0.4. The component of Hubble constant responsible for expansion of the universe is 40% of H0 and for the tired light is 60% of H0. Consequently, the critical density is only 16% of its currently accepted value; a lot less dark matter is needed to make up the critical density. In addition, the best data fit yields the cosmological constant density parameter =0. The tired light effect may thus be considered equivalent to the cosmological constant in the hybrid model.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.007 | 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".