Properties of galaxies with an offset between the position angles of the major kinematic and photometric axes
Bibliographic record
Abstract
We derive the photometric, kinematic, and abundance characteristics of 18 star-forming MaNGA galaxies with fairly regular velocity fields and surface brightness distributions and with a large offset between the measured position angles of the major kinematic and photometric axes, ΔPA ≳ 20°. The aim is to examine if there is any other distinctive characteristic common to these galaxies. We found morphological signs of interaction in some (in 11 out of 18) but not in all galaxies. The observed velocity fields show a large variety; the maps of the isovelocities vary from an hourglass-like appearance to a set of straight lines. The position angles of the major kinematic axes of the stellar and gas rotations are close to each other. The values of the central oxygen abundance, radial abundance gradient, and star formation rate are distributed within the intervals defined by galaxies with small (no) ΔPA of similar mass. Thus, we do not find any specific characteristic common to all galaxies with large ΔPA. Instead, the properties of these galaxies are similar to those of galaxies with small (no) ΔPA. This suggests that either the reason responsible for the large ΔPA does not influence other characteristics or the galaxies with large ΔPA do not share a common origin, they can, instead, originate through different channels.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".