ON THE FORM OF THE<i>SPITZER</i>LEAVITT LAW AND ITS DEPENDENCE ON METALLICITY
Bibliographic record
Abstract
The form and metallicity dependence of Spitzer mid-infrared Cepheid relations are a source of debate. Consequently, Spitzer 3.6 and 4.5 μm period–magnitude and period–color diagrams were re-examined via robust routines, thus providing an alternative interpretation to consider. The relations (nearly mean-magnitude) appear non-linear over an extensive baseline (0.45 < log P 0 < 2.0), particularly the period–color trend, which to first order follows constant (3.6–4.5) color for shorter-period Cepheids and may transition into a bluer convex trough at longer periods. The period–magnitude functions can be described by polynomials (e.g., [3.6 μm] = K 0 − (3.071 ± 0.059)log P 0 − (0.120 ± 0.032)log P 0 2 ), and Cepheid distances computed using 3.6 and 4.5 μm relations agree with each other and the latter provides a first-order consistency check (CO sampled at 4.5 μm does not seriously compromise those distances). The period–magnitude relations appear relatively insensitive to metallicity variations ([Fe/H] ∼ 0 to −0.75 |γ| < 0.1 mag dex −1 ), a conclusion inferred partly from comparing galaxy distances established from those relations and NED-D ( n > 700), yet a solid conclusion awaits comprehensive mid-infrared observations for metal-poor Cepheids in IC 1613 ([Fe/H] ∼ -1). The Cepheid-based distances were corrected for dust obscuration using a new ratio (i.e., A 3.6 / E B − V = 0.18 ± 0.06) deduced from GLIMPSE ( Spitzer ) data.
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 | 0.001 | 0.011 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".