Galaxy Quenching from Cosmic Web Detachment
Bibliographic record
Abstract
We propose the Cosmic Web Detachment (CWD) model, a framework to interpret the star-formation history of galaxies in a cosmological context. The CWD model unifies several starvation mechanisms known to disrupt or stop star formation into one single physical framework. Galaxies begin accreting star-forming gas at early times via a network of primordial filaments, simply related to the pattern of density fluctuations in the initial conditions. But when streams cross on intergalactic scales, this pattern is disrupted, and the galaxy detaches from its primordial filaments, ending the accretion of cold gas. We argue that CWD encompasses known external processes halting star formation, such as harassment, strangulation and starvation. On top of these external processes, internal feedback processes such as AGN contribute to stop in star formation as well. We introduce a simple formalism to identify CWD events and quenched galaxies in dark-matter N-body simulations. With it we reproduce and explain, in the context of CWD, several observations including downsizing, the cosmic star formation rate history, the galaxy mass-color diagram and the dependence of the fraction of red galaxies with mass and local density.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".