Bibliographic record
Abstract
Abstract. Despite much work, the connection between dwarf elliptical galaxies (dEs) and dwarf irregulars (dIs) remains unclear. Recently, we found that the surface brightness profiles (SBPs) of dIs in the near-infrared can be well fitted with a hyperbolic secant (sech) function. From sech fits, a tight relationship was derived between the absolute magnitude, central surface brightness, and 21cm line widths, which amounts to a fundamental plane for dIs. Here we examine how closely dEs fit into the dI fundamental plane using published data for 22 dEs in the Virgo cluster and the Local Group. Over a 9 mag interval in absolute magnitude the dEs fall in the plane defined by the dIs. The outstanding overlap suggests more than a casual relationship between the two classes. 1. The dI Sample A sample of 19 field dIs with very accurate distances was observed at CFHT adopting a prudent approach to sample the faint outer regions (Vaduvescu and McCall 2004). We separated resolved and unresolved components using the KILLALL package (Buta and McCall 1999) and then derived the surface brightness profiles (SBPs) by fitting ellipses using the stsdas/ellipse function in IRAF. The hyperbolic secant function (sech) was found to fit accurately all the SBPs in our dI sample (Vaduvescu et al. 2005): I = I0 sech(r/r0) =
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".