Clustering of the AKARI NEP deep field 24iμ/im selected galaxies
Bibliographic record
Abstract
piAims./i We present a method of selection of 24 iμ/im galaxies from the AKARI north ecliptic pole (NEP) deep field down to 150 iμ/iJy and measurements of their two-point correlation function. We aim to associate various 24 iμ/im selected galaxy populations with present day galaxies and to investigate the impact of their environment on the direction of their subsequent evolution./p piMethods./i We discuss using of Support Vector Machines (SVM) algorithm applied to infrared photometric data to perform star-galaxy separation, in which we achieve an accuracy higher than 80%. The photometric redshift information, obtained through the CIGALE code, is used to explore the redshift dependence of the correlation function parameter (rsub0/sub) as well as the linear bias evolution. This parameter relates galaxy distribution to the one of the underlying dark matter. We connect the investigated sources to their potential local descendants through a simplified model of the clustering evolution without interactions./p piResults./i We observe two different populations of star-forming galaxies, at zsubmed/sub ∼ 0.25, zsubmed/sub ∼ 0.9. Measurements of total infrared luminosities (iL/isubTIR/sub) show that the sample at zsubmed/sub ∼ 0.25 is composed mostly of local star-forming galaxies, while the sample at zsubmed/sub ∼ 0.9 is composed of luminous infrared galaxies (LIRGs) with iL/isubTIR/sub ∼ 10sup11.62/sup iL/isub⨀/sub. We find that dark halo mass is not necessarily correlated with the iL/isubTIR/sub: for subsamples with iL/isubTIR/sub = 10sup11.15/sup iL/isub⨀/sub at zsubmed/sub ∼ 0.7 we observe a higher clustering length (ir/isub0/sub = 6.21 ± 0.78 [ih/isup−1/supMpc]) than for a subsample with mean iL/isubTIR/sub = 10sup11.84/sup iL/isub⨀/sub at zsubmed/sub ∼ 1.1 (ir/isub0/sub = 5.86 ± 0.69 ih/isup−1/supMpc). We find that galaxies at zsubmed/sub ∼ 0.9 can be ancestors of present day iL/isub∗/sub early type galaxies, which exhibit a very high ir/isub0/sub ∼ 8ih/isup−1/sup Mpc./p
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.005 |
| 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 teacher head, 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".