Number Density Evolution of<i>K</i><sub><i>s</i></sub>‐Band–Selected High‐Redshift Galaxy Populations in the<i>AKARI</i>North Ecliptic Pole Field
Bibliographic record
Abstract
We present the number counts of K s -band-selected high-redshift galaxy populations such as extremely red objects (EROs), B -, z -, and K -band-selected galaxies (BzKs) and distant red galaxies (DRGs) in the AKARI NEP field. These high-redshift galaxy samples are extracted from a multicolor catalog combining optical data from Suprime-Cam on the 8.2 m Subaru Telescope with near-infrared data from the Florida Multiobject Imaging Near-IR Grism Observational Spectrometer on the Kitt Peak National Observatory 2.1 m telescope over 540 arcmin 2 in the NEP region field. The final catalog contains 308 EROs ( K s < 19.0; 54% are dusty star-forming EROs, and the rest are passive old EROs), 137 star-forming BzKs, and 38 passive old BzKs ( K s < 19.0) and 64 DRGs ( K s < 18.6). We also produce individual component source counts for both the dusty star-forming and passive populations. We compare the observed number counts of the high redshift passively evolving galaxy population with a backward pure luminosity evolution (PLE) model allowing different degrees of number density evolution. We find that the PLE model without density evolution fails to explain the observed counts at faint magnitudes, while the model incorporating negative density evolution is consistent with the observed counts of the passively evolving population. We also compare our observed counts of dusty star-forming EROs with a phenomenological evolutionary model postulating that the near-infrared EROs can be explained by the source densities of the far-infrared-submillimeter populations. Our model predicts that the dusty ERO source counts can be explained assuming a 25% contribution of submillimeter star-forming galaxies with the majority of brighter K s -band-detected dusty EROs having luminous (rather than HR 10 type ultraluminous) submillimeter counterparts. We propose that the fainter K s > 19.5 population is dominated by the submillijansky submillimeter population. We also predict a turnover in dusty ERO counts around 19 < K s < 20.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".