Efficient Detection of Emission-line Galaxies in the Cl0016+1609 and MACSJ1621.4+3810 Supercluster Filaments Using SITELLE*
Bibliographic record
Abstract
Abstract We observe a system of filaments and clusters around Cl0016+1609 and MACSJ1621.4+3810 using the SITELLE Fourier transform spectrograph at the Canada–France–Hawaii Telescope. For Cl0016+1609 (z = 0.546), the observations span an 11.8 Mpc × 4.3 Mpc region along an eastern filament that covers the main cluster core, as well as two 4.3 Mpc × 4.3 Mpc regions that each cover southern subclumps. For MACSJ1621.4+3810 (z = 0.465), 3.9 Mpc × 3.9 Mpc around the main cluster core is covered. We present the frequency and location of the emission-line galaxies and their emission-line images, and calculate the star formation rates, specific star formation rates, and merger statistics. In Cl0016+1609, we find 13 [O ii] 3727 Å emitting galaxies with star formation rates between 0.2 and 14.0 M ⊙ yr−1. Of these, % are found in regions with moderate local galaxy density, avoiding the dense cluster cores. These galaxies follow the main filament of the superstructure and are mostly blue and disky, with several showing close companions and merging morphologies. In MACSJ1621.4+3810, we find 10 emission-line sources. All are blue ( %), with % classified as disky and % as merging systems. Eight avoid the cluster core ( %), but two ( %) are found near high-density regions, including the brightest cluster galaxy (BCG). These observations push the spectroscopic study of galaxies in filaments beyond z ∼ 0.3 to z ∼ 0.5. Their efficient confirmation is paramount to their usefulness as more galaxy surveys come online.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".