Normal galaxies in the <i>XMM-Newton</i> fields
Bibliographic record
Abstract
Context. We use the first XMM serendipitous source catalogue (1XMM) to compile a sample of normal X-ray galaxies.Aims. We seek to expand the database of X-ray selected normal galaxies at intermediate redshifts and examine the relation between X-ray emission and star formation for late-type systems.Methods. The candidates are selected based on their X-ray (soft spectra), X-ray to optical (log < -2) and optical (extended sources) properties. 44 candidates are found and 35 are spectroscopically observed with the Australian National University's 2.3 m telescope to examine their nature.Results. Of the 35 sources observed, 2 are AGN, 11 emission line galaxies, 12 absorption line galaxies, 6 have featureless spectra while 4 are associated with Galactic stars. We combine our emission line sample with earlier works forming the most comprehensive X-ray selected galaxy sample for the study of the X-ray luminosity to the Hα luminosity – a well-calibrated star-formation indicator – relation.Conclusions. We find that the X-ray luminosity strongly correlates with the Hα luminosity, suggesting that the X-rays efficiently trace the star-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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".