Multi-wavelength observations of planet forming disks: Constraints on planet formation processes
Bibliographic record
Abstract
Our understanding of protoplanetary disks has greatly improved over the last decade due to a wealth of data from new facilities. Unbiased dust surveys with Spitzer leave us with good constraints on the dust dispersal timescale of small grains in the terrestrial planet forming region. In the ALMA era, this can be confronted for the first time also with evolutionary timescales of mm grains in the outer disk. Gas surveys in the context of the existing multi-wavelength dust surveys will be a key in large statistical studies of disk gas evolution. Unbiased gas surveys are limited to ALMA CO submm surveys, where the quantitative interpretation is still debated. Herschel gas surveys have been largely biased, but [OI] 63 mic surveys and also accretion tracers agree qualitatively with the evolutionary timescale of small grains in the inner disk. Recent advances achieved by means of consistent multi-wavelength studies of gas AND dust in planet forming disks reveal the subtleties of the quantitative interpretation of gas surveys. Observational methods to determine disk masses e.g. from CO submm lines require the knowledge of the dust properties in the disk. Understanding not only the gas evolution, but also its chemical composition will provide crucial input for planet formation models. Kinetic chemical results give profoundly different answers than thermodynamic equilibrium in terms of the C/O ratios as well as the water ice/rock ratios. Again, dust has a key impact on the chemical evolution and composition of the gas. Grain growth for example affects freeze-out processes and strongly increases the cosmic ray induced UV field.
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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 | 0.000 | 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 | 0.000 | 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".