How the gradient of <i>M</i> d versus UV field strength yields insights into the ages of protoplanetary disc populations
Bibliographic record
Abstract
ABSTRACT Far-ultraviolet (UV) radiation from massive stars launches photoevaporative winds from the outer regions of protoplanetary discs around other stars, removing gas and dust. Observations have identified a relation between the median dust disc mass and the external UV field strength. Here, we use disc evolutionary models to explore how this relation evolves over time, and with respect to other stellar and disc properties. We find that the slope for the relationship $\lambda _{\rm UV}$ flattens over time as populations age, possibly explaining the differences seen between the L1641-N and L1641-S clusters in Orion A. We determine that $\lambda _{\rm UV}$ depends on the stellar mass, where more massive stars exhibit steeper gradients than their lesser counterparts, in agreement with the differences seen between Herbig and T Tauri stars. Additionally, the strength of the mechanism for angular momentum transport, either viscosity or magnetohydrodynamic disc winds, is found to significantly affect $\lambda _{\rm UV}$ with stronger $\alpha$ values reducing $\lambda _{\rm UV}$ due to more material accreting onto the central stars in weaker UV environments. Estimates of $\lambda _{\rm UV}$ from observations of L1641 place preliminary constraints on $\alpha$ to be between $10^{-3.5}$ and $10^{-2.5}$, consistent with literature estimates. Further observations in different regions and better classifications of stellar masses will allow us to place stringent constraints on disc evolution properties, improving our understanding of how protoplanetary discs evolve.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".