Bibliographic record
Abstract
A cosmology model is derived, forming an expanding, curved, unbounded, and finite universe resembling a three-dimensional hypersphere with positive curvature. Growth, curvature, and the expansion rate are forced by the initial conditions accompanying the emergence of space and time from the “big bang” singularity. The model generates several variables (past and present stellar distance, luminosity distance, time of emission, photon path, recession velocity, radiation temperature, universe circumference, and Hubble parameter) that are sole functions of redshift, z (readily measured by spectroscopic or photometric means). The model also presents two concepts that replace the need for cosmic inflation and dark energy. Equations for luminosity distance, dL, and Hubble parameter, H, compare extremely well with 28 values of baryon acoustic oscillation measured data over the redshift range 0.07 < z < 2.3. A second data set, compiled by NASA, consists of 27 000 type 1a supernovae measurements of luminosity distance and redshift (0.001 < z < 10). Although the data are extremely scattered, within the scatter is a narrow, well-defined core whose distance, [Formula: see text], exceeds the model value, dL, as redshift increases. The larger distance, [Formula: see text], resulting from a weaker than expected optical signal, is commonly explained as due to an acceleration of universe expansion. Alternatively, if the photons are assumed to be partially quenched by cosmic dust, in proportion to the distance travelled, the weakened core signal can be described by a radiative transfer equation. The resulting equation for [Formula: see text], with an extinction coefficient of 0.000 345 Mpc−1 (or a photon mean free path of 2900 Mpc), fits the core data perfectly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".