From the Intergalactic to the Interstellar Scales – EQUALS: a High-resolution Legacy Survey of Gas in the Distant Universe Using ESPRESSO
Bibliographic record
Abstract
Understanding how the Universe evolved from diffuse primordial gas into the rich cosmic web we observe today is one of the great challenges of modern astrophysics. Quasar absorption lines — the imprints left by intervening gas on the light from distant quasars — provide key diagnostics of many aspects of this investigation, ranging from fundamental physics to cosmology and galaxy formation. The unprecedented combination of extremely precise wavelength calibration, high spectral resolution and high sensitivity of the Echelle SPectrograph for Rocky Exoplanet and Stable Spectroscopic Observations (ESPRESSO) has finally enabled observations that will further constrain both state-of-the-art cosmological simulations of galaxy evolution and theoretical stellar nucleosynthetic yields. In this article, we present the ESPRESSO Quasar Absorption Line Survey (EQUALS), an ESO Large Programme, designed to tackle several outstanding questions from constraining the properties of dark matter at the smallest scales probed by the Lyman-alpha forest to determining the temperature of the intergalactic medium at z ~ 4 and precisely quantifying the chemical contributions of stellar populations in the early Universe. EQUALS will provide a legacy sample of deep spectra to showcase ESPRESSO capabilities to the quasar absorption line community whilst providing epoch measurements for the key science goals of upcoming spectroscopic instrumentation on the next generations of telescopes.
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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 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".