Caltech Faint Galaxy Redshift Survey. XV. Classifications of Galaxies with 0.2 < [CSC]z[/CSC] < 1.1 in the Hubble Deep Field North and its Flanking Fields
Bibliographic record
Abstract
To circumvent the spatial effects of resolution on galaxy classification, the images of 233 objects of known redshift in the Hubble Deep Field (HDF) and its flanking fields that have redshifts in the range 0.20 < z < 1.10 were degraded to the resolution that they would have had if they were all located at a redshift of z = 1.00. As in Paper XIV of the present series, the effects of shifts in rest wavelength were mitigated by using R -band images for the classification of galaxies with 0.2 < z < 0.6 and I -band images for objects with redshifts 0.6 < z < 1.1. A special effort was made to search for bars in distant galaxies. The present data strongly confirm the previous conclusion that the Hubble tuning fork diagram only provides a satisfactory framework for the classification of galaxies with z < 0.3. More distant disk galaxies are often difficult to shoehorn into the Hubble classification scheme. The paucity of barred spirals and grand-design spirals at large redshifts is confirmed. It is concluded that the morphology of disk galaxies observed at look-back times smaller than 3–4 Gyr differs systematically from that of more distant galaxies viewed at look-back times of 4–8 Gyr. The disks of late-type spirals at z > 0.5 are seen to be more chaotic than those of their nearer counterparts. Furthermore, the spiral structure in distant early-type spirals appears to be less well developed than it is in nearby early galaxies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.015 |
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".