GHASP: an Hα kinematic survey of spiral and irregular galaxies – VI. New Hα data cubes for 108 galaxies
Bibliographic record
Abstract
Abstract We present the Fabry–Perot observations obtained for a new set of 108 galaxies in the frame of the Gassendi Hα survey of SPirals (GHASP). The GHASP survey consists of 3D Hα data cubes for 203 spiral and irregular galaxies, covering a large range in morphological types and absolute magnitudes, for kinematics analysis. The new set of data presented here completes the survey. The GHASP sample is by now the largest sample of Fabry–Perot data ever published. The analysis of the whole GHASP sample will be done in forthcoming papers. Using adaptive binning techniques based on Voronoi tessellations, we have derived Hα data cubes from which are computed Hα maps, radial velocity fields as well as residual velocity fields, position–velocity diagrams, rotation curves and the kinematical parameters for almost all galaxies. Original improvements in the determination of the kinematical parameters, rotation curves and their uncertainties have been implemented in the reduction procedure. This new method is based on the whole 2D velocity field and on the power spectrum of the residual velocity field rather than the classical method using successive crowns in the velocity field. Among the results, we point out that morphological position angles have systematically higher uncertainties than kinematical ones, especially for galaxies with low inclination. The morphological inclination of galaxies having no robust determination of their morphological position angle cannot be constrained correctly. Galaxies with high inclination show a better agreement between their kinematical inclination and their morphological inclination computed assuming a thin disc. The consistency of the velocity amplitude of our rotation curves has been checked using the Tully–Fisher relationship. Our data are in good agreement with previous determinations found in the literature. Nevertheless, galaxies with low inclination have statistically higher velocities than expected and fast rotators are less luminous than expected.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".