LATIS Data Release: $\sim4200$ Spectra of $z \sim 2-3$ Galaxies, Redshifts, and Intergalactic Medium Tomography Maps
Bibliographic record
Abstract
We present the data release of the Ly$α$ Tomography IMACS Survey (LATIS), one of the largest optical spectroscopic surveys of faint high-redshift galaxies. The survey provides 7408 optical spectra of candidate $z \sim 2-3$ galaxies and QSOs in the Canada-France-Hawaii Telescope Legacy Survey D1, D2 (COSMOS), and D4 fields. The $R \sim 1000$ spectra were obtained using the Inamori Magellan Areal Camera and Spectrograph (IMACS) at the Magellan Baade telescope, with typical integrations of 12 hr. From these spectra, we measured 5575 high-confidence spectroscopic redshifts, of which 4176 are at $z > 1.7$, thereby substantially increasing the number of public spectroscopic redshifts at $z \approx 2-3$ in COSMOS and the other survey fields. The data release includes Ly$α$ transmission fluctuations measured in $4.7 \times 10^5$ pixels, which were used to create 3D maps of the intergalactic medium (IGM) transmission spanning 1.65 deg$^2$ and $z = 2.2-2.8$ at a resolution of 4 $h^{-1}$ cMpc. These are the largest such maps to date and provide a novel tracer of large-scale structure in legacy fields. We also provide ancillary data, including mock surveys. The LATIS data will enable a variety of community studies of galaxy evolution, environments, and the IGM around cosmic noon.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.052 |
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".