Bibliographic record
Abstract
Cosmicflows is an ambitious program to map the velocity and density fields of the nearby universe. The current dissertation is a part of the Cosmicflows-4 project with the aim of measuring distances of more than 10,000 spiral galaxies in the local universe up to ~15,000 km/s. New HI linewidth information has come primarily from the Arecibo Legacy Fast ALFA Survey. Photometry of the sample galaxies has been carried out in optical (SDSS ugriz) and infrared (WISE W1 and W2) bands. Inclinations have been determined using an online graphical interface accessible to a collaboration of citizen scientists. Galaxy distances are measured based on the correlation between the rotation rate of spirals and their absolute luminosity, known as the Tully-Fisher Relation (TFR). I present the calibration of the TFR using a sub-sample of ~600 spirals located in 20 galaxy clusters. Correlations among observables such as color, surface brightness, and relative HI content are explored in attempts to reduce the scatter about the TFR with the goal of obtaining more accurate distances. I address the color-dependent discrepancies between measured distances at different wavebands. I study the dependency of the global intrinsic extinction in spiral galaxies on their morphologies, sizes, and spatial inclinations, using a subsample of ~2,200 galaxies with optical and infrared photometry information. I present two models for dust obscuration, a parametric model and a non-parametric model based on the Gaussian process formalism. An average dust attenuation curve is derived in the wavelengths range 0.36 to 4.5 microns. Finally, an algorithm to find nearby galaxy groups within 3,500 \kms (~45 Mpc) is presented. This algorithm is based on the observed scaling correlations that relate luminosity, velocity dispersion and dimensions of galaxy groups. Applying these scaling relations, in an iterative process, galaxies with almost the same radial velocities and in close angular proximity fall into groups. The most remarkable result of the study emerges from the construction of the halo mass function from the sample. At ~10^12 solar mass, there is a jog from the expectation Sheth-Tormen function, such that halo counts drop by a factor ~3 in all lower mass bins.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".