The<i>Hubble Space Telescope</i>Key Project on the Extragalactic Distance Scale. XXVI. The Calibration of Population II Secondary Distance Indicators and the Value of the Hubble Constant
Bibliographic record
Abstract
A Cepheid-based calibration is derived for four distance indicators that utilize stars in old stellar populations: the tip of the red giant branch (TRGB), the planetary nebula luminosity function (PNLF), the globular cluster luminosity function (GCLF), and the surface brightness fluctuation method (SBF). The calibration is largely based on the Cepheid distances to 18 spiral galaxies within cz = 1500 km s -1 obtained as part of the Hubble Space Telescope ( HST ) Key Project on the Extragalactic Distance Scale, but relies also on Cepheid distances from separate HST and ground-based efforts. The newly derived calibration of the SBF method is applied to obtain distances to four Abell clusters in the velocity range 3800-5000 km s -1 . Combined with cluster velocities corrected for a cosmological flow model, these distances imply a value of the Hubble constant of H 0 = 69 ± 4 (random) ± 6 (systematic) km s -1 Mpc -1 . This result assumes that the Cepheid PL relation is independent of the metallicity of the variable stars; adopting a metallicity correction as in Kennicutt et al. would produce a 5% ± 3% decrease in H 0 . Finally, the newly derived calibration allows us to investigate systematics in the Cepheid, PNLF, SBF, GCLF, and TRGB distance scales.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.018 |
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".