Bibliographic record
Abstract
We present observational evidence for the inhibition of bar formation in dispersion-dominated (dynamically hot) galaxies by studying the relationship between galactic structure and host galaxy kinematics in a sample of 257 galaxies between 0.1 < z ⩽ 0.84 from the All-Wavelength Extended Groth Strip International Survey and the Deep Extragalactic Evolutionary Probe 2 survey. We find that bars are preferentially found in galaxies that are massive and dynamically cold (rotation-dominated) and on the stellar Tully–Fisher relationship, as is the case for barred spirals in the local universe. The data provide at least one explanation for the steep ( × 3) decline in the overall bar fraction from z = 0 to z = 0.84 in L * and brighter disks seen in previous studies. The decline in the bar fraction at high redshift is almost exclusively in the lower mass (10 < log M * ( M ☉ ) < 11), later-type, and bluer galaxies. A proposed explanation for this "downsizing" of the bar formation/stellar structure formation is that the lower mass galaxies may not form bars because they could be dynamically hotter than more massive systems from the increased turbulence of accreting gas, elevated star formation, and/or increased interaction/merger rate at higher redshifts. The evidence presented here provides observational support for this hypothesis. However, the data also show that not every disk galaxy that is massive and cold has a stellar bar, suggesting that mass and dynamic coldness of a disk are necessary but not sufficient conditions for bar formation—a secondary process, perhaps the interaction history between the dark matter halo and the baryonic matter, may play an important role in bar formation.
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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 | 0.000 |
| 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) | 0.002 | 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".