Environmental dependence of 8 μm luminosity functions of galaxies at z ~ 0.8: Comparison between RXJ1716.4+6708 and the AKARI NEP-deep field
Why this work is in the frame
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Bibliographic record
Abstract
Aims. We aim to reveal environmental dependence of infrared luminosity functions (IR LFs) of galaxies at z ~ 0.8 using the AKARI \nsatellite. AKARI’s wide field of view and unique mid-IR filters help us to construct restframe 8 μm LFs directly without relying on \nSED models. \nMethods. We construct restframe 8 μm IR LFs in the cluster region RXJ1716.4+6708 at z = 0.81, and compare them with a blank \nfield using the AKARI north ecliptic pole deep field data at the same redshift. AKARI’s wide field of view (10' × 10') is suitable to \ninvestigate wide range of galaxy environments. AKARI’s 15 μm filter is advantageous here since it directly probes restframe 8 μm at \nz ~ 0.8, without relying on a large extrapolation based on a SED fit, which was the largest uncertainty in previous work. \nResults. We have found that cluster IR LFs at restframe 8 μm have a factor of 2.4 smaller L^∗ and a steeper faint-end slope than that \nof the field. Confirming this trend, we also found that faint-end slopes of the cluster LFs becomes flatter and flatter with decreasing \nlocal galaxy density. These changes in LFs cannot be explained by a simple infall of field galaxy population into a cluster. Physics \nthat can preferentially suppress IR luminous galaxies in high density regions is required to explain the observed results.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it