Line confusion in spectroscopic surveys and its possible effects: shifts in Baryon Acoustic Oscillations position
Bibliographic record
Abstract
ABSTRACT Roman Space Telescope will survey about 17 million emission-line galaxies over a range of redshifts. Its main targets are Hα emission-line galaxies at low redshifts (z < 2) and [O iii] emission-line galaxies at high redshifts (z > 2). The Roman Space Telescope will estimate the redshift of these galaxies with single-line identification. This suggests that other emission-line galaxies may be misidentified as the main targets. In particular, it is hard to distinguish between the H β and [O iii] lines as the two lines are close in wavelength and hence the photometric information may not be sufficient to separate them reliably. Misidentifying H β emitter as [O iii] emitter will cause a shift in the inferred radial position of the galaxy by approximately 90 Mpc h−1. This length-scale is similar to the Baryon Acoustic Oscillation (BAO) scale and could shift and broaden the BAO peak, possibly introduce errors in determining the BAO peak position. We qualitatively describe the effect of this new systematic and further quantify it with a light-cone simulation with emission-line galaxies. Our results show a systematic shift in the recovered isotropic BAO positions that depends on the percentage of interlopers (percentage of ${\rm H}\,\beta$) in the sample. The systematic shift can be as large as $0.1{-}0.3\,\mathrm{ per}\,\mathrm{ cent} \, {\rm x}\, {{\%}}{\rm H}\,\beta$ for analysis performed at redshifts z = 1.3−1.9.
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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 | 0.006 | 0.031 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".