Explorations in Hubble Space: A Quantitative Tuning Fork
Bibliographic record
Abstract
In order to establish an objective framework for studying galaxy morphology, we have developed a quantitative two-parameter description of galactic structure that maps closely onto Hubble's original tuning fork. Any galaxy can be placed in this "Hubble space," where the x -coordinate measures position along the early-to-late sequence while the y -coordinate measures in a quantitative way the degree to which the galaxy is barred. The parameters defining Hubble space are sufficiently robust to allow the formation of Hubble's tuning fork to be mapped out to high redshifts. In the present paper, we describe a preliminary investigation of the distribution of local galaxies in Hubble space based on the CCD imaging atlas published by Frei et al. in 1996. We find that barred, weakly barred, and unbarred galaxies are remarkably well separated on this diagnostic diagram. The spiral sequence is clearly bimodal and indeed approximates a tuning fork: strongly barred and unbarred spirals do not simply constitute the extrema of a smooth unimodal distribution of bar strength but, rather, populate two parallel sequences. Strongly barred galaxies lie on a remarkably tight sequence, strongly suggesting the presence of an underlying unifying physical process. Rather surprisingly, weakly barred systems do not seem to correspond to objects bridging the parameter space between unbarred and strongly barred galaxies but, instead, form an extension of the regular spiral sequence. This relation lends support to models in which the bulges of late-type spirals originate from secular processes driven by bars.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".