Unique Tracks Drive the Scatter of the Spatially Resolved Star Formation Main Sequence
Why this work is in the frame
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Bibliographic record
Abstract
The scatter of the spatially resolved star formation main sequence (SFMS) is investigated in order to reveal signatures about the processes of galaxy formation and evolution. We have assembled a sample of 355 nearby galaxies with spatially resolved H and mid-infrared fluxes from the Survey for Ionized Neutral Gas in Galaxies and the Wide-field Infrared Survey Explorer, respectively. We examine the impact of various star formation rate (SFR) and stellar mass transformations on the SFMS. Ranging from 106 to 1011.5 M o and derived from color to mass-to-light ratio methods for mid-infrared bands, the stellar masses are internally consistent within their range of applicability and inherent systematic errors; a constant mass-to-light ratio also yields representative stellar masses. The various SFR estimates show intrinsic differences and produce noticeable vertical shifts in the SFMS, depending on the timescales and physics encompassed by the corresponding tracer. SFR estimates appear to break down on physical scales below 500 pc. We also examine the various sources of scatter in the spatially resolved SFMS and find morphology does not play a significant role. We identify three unique tracks across the SFMS by individual galaxies, delineated by a critical stellar mass density of log ∼ 7.5. Below this scale, the SFMS shows no clear trend and is likely driven by local, stochastic internal processes. Above this scale, all spatially resolved galaxies have comparable SFMS slopes but exhibit two different behaviors, resulting likely from the rate of mass accretion at the center of the galaxy.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it