The Subaru FMOS galaxy redshift survey (FastSound). I. Overview of the survey targeting Hα emitters at <i>z</i> ∼ 1.4
Bibliographic record
Abstract
Abstract FastSound is a galaxy redshift survey that uses the near-infrared Fiber Multi-Object Spectrograph (FMOS) mounted on the Subaru Telescope, targeting Hα emitters at z ∼ 1.18–1.54 down to the sensitivity limit of Hα flux ∼ 2 × 10−16 erg cm−2 s−1. The primary goal of the survey is to detect redshift space distortion (RSD), to test the general theory of relativity by measuring the growth rate of large-scale structure and to constrain modified gravity models for the origin of the accelerated expansion of the universe. The target galaxies were selected based on photometric redshifts and Hα flux estimates calculated by fitting spectral energy distribution (SED) models to the five optical magnitudes of the Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) Wide catalog. The survey started in 2012 March, and all the observations were completed in 2014 July. In total, we achieved 121 pointings of FMOS (each pointing has a 30′ diameter circular footprint) covering 20.6 deg2 by tiling the four fields of the CFHTLS Wide in a hexagonal pattern. Emission lines were detected from ∼ 4000 star-forming galaxies by an automatic line detection algorithm applied to 2D spectral images. This is the first in a series of papers based on FastSound data, and we describe the details of the survey design, target selection, observations, data reduction, and emission line detections.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".