Preprint typeset using L ATEX style emulateapj v. 08/22/09 BROADBAND IMAGING SEGREGATION OF z ∼ 3 Lyα EMITTING AND Lyα ABSORBING GALAXIES
Bibliographic record
Abstract
The spectral properties of Lyman break galaxies (LBGs) offer a means to isolate pure samples displaying either dominant Lyα in absorption or Lyα in emission using broadband information alone. We present criteria developed using a large z ∼ 3 LBG spectroscopic sample from the literature that enables large numbers of each spectral type to be gathered in photometric data, providing good statistics for multiple applications. In addition, we find that the truncated faint, blue-end tail of z ∼ 3 LBG population overlaps and leads directly into an expected Lyα emitter (LAE) population. As a result, we present simple criteria to cleanly select large numbers of z ∼ 3 LAEs in deep broadband surveys. We present the spectroscopic results of 32 r ′ � 25.5 LBGs and r ′ � 27.0 LAEs at z ∼ 3 pre-selected in the Canada-France-Hawaii Telescope Legacy Survey that confirm these criteria.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.769 | 0.687 |
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".