Doubly Discordant S$$\boldsymbol{H_{0}}$$ES NGC 4258 Cepheid Relations ($$\boldsymbol{HVI}$$) and Impactful Extinction Laws
Bibliographic record
Abstract
S $$H_{0}$$ ES (Supernovae and $$H_{0}$$ for the Equation of State of dark energy) 2016–2022 $$HVI$$ data for classical Cepheids in the keystone galaxy NGC 4258 yield doubly discordant Wesenheit Leavitt functions: $$\Delta W_{0,H-VI}=-0\overset{\textrm{m}}{.}13\pm 0\overset{\textrm{m}}{.}02$$ ( $$-0\overset{\textrm{m}}{.}17$$ unweighted) and that is paired with the previously noted $$\Delta W_{0,I-VI}\simeq-0\overset{\textrm{m}}{.}3$$ , which in concert with complimentary evidence suggest the 2016 S $$H_{0}$$ ES NGC 4258-anchored $$H_{0}\pm\sigma_{H_{0}}$$ warrants scrutiny (i.e., $$\sigma_{H_{0}}/{H_{0}}\gtrsim 6\%$$ ). Cepheid distance uncertainties are further exacerbated by extinction law ambiguities endemic to such Leavitt relations (e.g., NGC 4258), particularly for comparatively obscured variables (e.g., $$\Delta d\gtrsim 4\%$$ , reddened Cepheid subsamples in the Milky Way, M 31, NGC 2442, NGC 4424, NGC 5643, NGC 7250). Lastly, during the analysis it was identified that the 2022 S $$H_{0}$$ ES database relays incorrect SMC Cepheid photometry.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".