Intensity mapping from the sky: synergizing the joint potential of [O <scp>iii</scp>] and [C <scp>ii</scp>] surveys at reionization
Bibliographic record
Abstract
ABSTRACT We forecast the ability of future-generation experiments to detect the fine-structure lines of the carbon and oxygen ions, [C ii] and [O iii] in intensity mapping (IM) from the Epoch of Reionization (z ∼ 6–8). Combining the latest empirically derived constraints relating the luminosity of the [O iii] line to the ambient star formation rate, and using them in conjunction with previously derived estimates for the abundance of [C ii] in haloes, we predict the expected autocorrelation IM signal to be observed using new experiments based on the Fred Young Submillimetre Telescope (FYST) and the balloon-borne facility, Experiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) over z ∼ 5.3–7. We describe how improvements to both the ground-based and balloon-based surveys in the future will enable a cross-correlation signal to be detected at ∼10–30σ over z ∼ 5.3–7. Finally, we propose a space-based mission targeting the [O iii] 88 and 52 $\mu$m lines along with the [C ii] 158 $\mu$m line, configured to enhance the signal-to-noise ratio of cross-correlation measurements. We find that such a configuration can achieve a high-significance detection (hundreds of σ) in both auto and cross-correlation modes.
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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 | 0.002 |
| 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) | 0.001 | 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".