Dark Energy Survey Year 1 Results: A Precise H0 Estimate from DES Y1, BAO, and D/H Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We combine Dark Energy Survey Year 1 clustering and weak lensing data with baryon acoustic oscillations and Big Bang nucleosynthesis experiments to constrain the Hubble constant. Assuming a flat ΛCDM model with minimal neutrino mass (∑mν = 0.06 eV), we find |$H_0=67.4^{+1.1}_{-1.2}\ \rm {km\,\rm s^{-1}\,\rm Mpc^{-1}}$| (68 per cent CL). This result is completely independent of Hubble constant measurements based on the distance ladder, cosmic microwave background anisotropies (both temperature and polarization), and strong lensing constraints. There are now five data sets that: (a) have no shared observational systematics; and (b) each constrains the Hubble constant with fractional uncertainty at the few-per cent level. We compare these five independent estimates, and find that, as a set, the differences between them are significant at the 2.5σ level (χ2/dof = 24/11, probability to exceed = 1.1 per cent). Having set the threshold for consistency at 3σ, we combine all five data sets to arrive at |$H_0=69.3^{+0.4}_{-0.6}\ \rm {km\,\mathrm{ s}^{-1}\,\mathrm{ Mpc}^{-1}}$|.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it