The cosmological bias factor of damped Lyman alpha systems: dependence on metal line strength
Bibliographic record
Abstract
We measure the cosmological bias factor of damped Ly α absorbers (DLAs) from their cross-correlation with the Ly α forest absorption, as a function of the DLA metal strength, defined from an average of equivalent widths of the strongest detectable low-ionization metal lines. A clear increase of the bias factor with metal strength is detected, as expected from a relation of metallicity and velocity dispersion with host halo mass. The relation is stronger after the metal strength is corrected for the H i column density, to make it more related to metallicity instead of metal column density. After correcting for the effects of measurement errors of the metal strength parameter, we find that the bias factor of DLAs with the weakest metal lines is close to unity, consistent with an origin in dwarf galaxies with host halo masses |${\sim } 10^{10}\, {\rm M_\odot }$|, whereas the most metal rich DLAs have a bias factor as large as bDLA ∼ 3, indicative of massive galaxies or galaxy groups in host haloes with masses |${\sim } 10^{12}\, {\rm M_\odot }$|. Our result confirms the physical origin of the relation of bias factors measured from cross-correlation studies to the host haloes of the absorbers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".