A CATALOG OF DETAILED VISUAL MORPHOLOGICAL CLASSIFICATIONS FOR 14,034 GALAXIES IN THE SLOAN DIGITAL SKY SURVEY
Bibliographic record
Abstract
We present a catalog of detailed visual classifications for 14,034 galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 4 (DR4). Our sample includes nearly all spectroscopically targeted galaxies in the redshift range 0.01 < z < 0.1 down to an apparent extinction-corrected limit of g < 16 mag. In addition to T-Types, we record the existence of bars, rings, lenses, tails, warps, dust lanes, arm flocculence, and multiplicity. This sample defines a comprehensive local galaxy sample which we will use in future papers to study low-redshift morphology. It will also prove useful for calibrating automated galaxy classification algorithms. In this paper, we describe the classification methodology used, detail the systematics and biases of our sample, and summarize the overall statistical properties of the sample, noting the most obvious trends that are relevant for general comparisons of our catalog with previously published work.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".