MusE GAs FLOw and Wind (MEGAFLOW)
Bibliographic record
Abstract
Absorption line spectroscopy using background quasars can provide strong constraints on galactic outflows. In this paper we investigate possible scaling relations between outflow properties, namely outflow velocity Vout, mass ejection rate Ṁout, and mass loading factor η, and the host galaxy properties, such as star formation rate (SFR), SFR surface density, redshift, and stellar mass, using galactic outflows probed by background quasars from MEGAFLOW and other surveys. We find that Vout (η) is (anti-)correlated with SFR and SFR surface density. We extend the formalism of momentum-driven outflows from a previous study to show that it applies not only to “down-the-barrel” studies, but also to winds probed by background quasars, suggesting a possible universal wind formalism. Under this formalism, we find a clear distinction between strong and weak outflows where strong outflows seem to have tighter correlations with galaxy properties (SFR or galaxy stellar mass) than weak outflows.
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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 | 0.001 | 0.001 |
| 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".