The<i>Hubble Space Telescope</i>Key Project on the Extragalactic Distance Scale. XXIV. The Calibration of Tully‐Fisher Relations and the Value of the Hubble Constant
Bibliographic record
Abstract
This paper presents the calibration of BVRIH -0.5 Tully-Fisher relations based on Cepheid distances to 21 galaxies within 25 Mpc and 23 clusters within 10,000 km s -1 . These relations have been applied to several distant cluster surveys in order to derive a value for the Hubble constant, H 0 , mainly concentrating on an I -band all-sky survey by Giovanelli and collaborators, consisting of total I magnitudes and 50% line width data for ~550 galaxies in 16 clusters. For comparison, we also derive the values of H 0 using surveys in the B and V bands by Bothun and collaborators, and in H band by Aaronson and collaborators. Careful comparisons with various other databases from the literature suggest that the H -band data, which have isophotal magnitudes extrapolated from aperture magnitudes rather than total magnitudes, are subject to systematic uncertainties. Taking a weighted average of the estimates of Hubble constants from four surveys, we obtain H 0 = 71 ± 4 (random) ± 7 (systematic). We have also investigated how the value of H 0 is affected by various systematic uncertainties, such as the internal extinction correction method used, Tully-Fisher slopes and shapes, a possible metallicity dependence of the Cepheid period-luminosity relation, and cluster population incompleteness bias.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.011 |
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".