THE MASSIVE SURVEY. I. A VOLUME-LIMITED INTEGRAL-FIELD SPECTROSCOPIC STUDY OF THE MOST MASSIVE EARLY-TYPE GALAXIES WITHIN 108 Mpc
Bibliographic record
Abstract
Massive early-type galaxies represent the modern-day remnants of the earliest major star formation episodes in the history of the universe. These galaxies are central to our understanding of the evolution of cosmic structure, stellar populations, and supermassive black holes, but the details of their complex formation histories remain uncertain. To address this situation, we have initiated the MASSIVE Survey, a volume-limited, multi-wavelength, integral-field spectroscopic (IFS) and photometric survey of the structure and dynamics of the ~100 most massive early-type galaxies within a distance of 108 Mpc. This survey probes a stellar mass range M* > 10^{11.5} Msun and diverse galaxy environments that have not been systematically studied to date. Our wide-field IFS data cover about two effective radii of individual galaxies, and for a subset of them, we are acquiring additional IFS observations on sub-arcsecond scales with adaptive optics. We are also acquiring deep K-band imaging to trace the extended halos of the galaxies and measure accurate total magnitudes. Dynamical orbit modeling of the combined data will allow us to simultaneously determine the stellar, black hole, and dark matter halo masses. The primary goals of the project are to constrain the black hole scaling relations at high masses, investigate systematically the stellar initial mass function and dark matter distribution in massive galaxies, and probe the late-time assembly of ellipticals through stellar population and kinematical gradients. In this paper, we describe the MASSIVE sample selection, discuss the distinct demographics and structural and environmental properties of the selected galaxies, and provide an overview of our basic observational program, science goals and early survey results.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".