The evolution of neutral gas in damped Lyman α systems from the XQ-100 survey
Bibliographic record
Abstract
We present a sample of 38 intervening damped Lyman α (DLA) systems identified towards 100 z > 3.5 quasars, observed during the XQ-100 survey.The XQ-100 DLA sample is combined with major DLA surveys in the literature.The final combined sample consists of 742 DLAs over a redshift range approximately 1.6 < z abs < 5.0.We develop a novel technique for computing DLA H I as a continuous function of redshift, and we thoroughly assess and quantify the sources of error therein, including fitting errors and incomplete sampling of the high column density end of the column density distribution function.There is a statistically significant redshift evolution in DLA H I (≥3σ ) from z ∼ 2 to z ∼ 5.In order to make a complete assessment of the redshift evolution of H I , we combine our high-redshift DLA sample with absorption surveys at intermediate redshift and 21-cm emission line surveys of the local universe.Although DLA H I , and hence its redshift evolution, remains uncertain in the intermediate-redshift regime (0.1 < z abs < 1.6), we find that the combination of high-redshift data with 21-cm surveys of the local universe all yield a statistically significant evolution in H I from z ∼ 0 to z ∼ 5 (≥3σ ).Despite its statistical significance, the magnitude of the evolution is small: a linear regression fit between H I and z yields a typical slope of ∼0.17 × 10 -3 , corresponding to a factor of ∼4 decrease in H I between z = 5 and z = 0.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".