<i>gzK</i>-colour-selected star-forming galaxies in the <i>AKARI</i> NEP-Deep Field
Bibliographic record
Abstract
ABSTRACT We study the clustering property and physical parameters of gzK-colour-selected star-forming galaxies (sgzKs) based on the Canada–France–Hawaii Telescope surveys over 0.55 deg2 in the AKARI North Ecliptic Pole-Deep Field. Two-point correlation functions for two magnitude-limited cases, Ks < 21.1 (N = 234) and Ks < 21.5 (N = 428), are estimated using a single power-law function with the fixed slope of 0.8. The bias factors of sgzKs with Ks < 21.1 and 21.5 are 5.79 ± 1.07 and 4.00 ± 0.67, respectively, representing that sgzKs with z ∼ 1.7 reside in dark matter haloes more massive than $10^{13} ~\rm M_{\odot }$. We find that haloes hosting sgzKs with Ks < 21.5 evolve into haloes that host local massive galaxies with ∼6 L*. This suggests that sgzKs with Ks < 21.5 are likely to be predecessors of local massive galaxies. The evolutionary track of bias factor for host haloes of the bright sgzKs is similar to that of the bright passive extremely red objects, implying a possible connection between the two populations of galaxies. From the spectral energy distribution fitting, we estimate physical parameters and active galactic nucleus (AGN) contribution for 75 mid-infrared (MIR)-detected sgzKs with Ks < 21.5. The median values of stellar mass and star formation rate are 9.5 × 1010$\rm M_{\odot }$ and 162 $\rm M_{\odot }$ yr−1, respectively. MIR-detected sgzKs have a variety of AGN contributions ranging from 0 to 80 per cent. The number ratio of sgzKs with larger AGN contribution than 10 per cent is 30 per cent.
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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 | 0.001 | 0.000 |
| 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".