The Pleiades Reflection Nebula. II. Simple Model Constraints on Dust Properties and Scattering Geometry
Bibliographic record
Abstract
We have used wide-field ultraviolet, optical, and far-infrared photometric images of Pleiades reflection nebulosity to analyze dust properties and the three-dimensional nebular geometry. Scattered light data were taken from 1650 and 2200 Å Wide-Field Imaging Survey Polarimeter images and a large 4400 Å mosaic of Burrell Schmidt CCD frames. Dust thermal emission maps were extracted from IRAS data. The scattering geometry analysis is complicated by the blending of light from many stars and the likely presence of more than one scattering layer. Despite these complications, we conclude that most of the scattered light comes from dust in front of the stars in at least two scattering layers, one far in front and extensive, the other nearer the stars and confined to areas of heavy nebulosity. The first layer can be approximated as an optically thin, foreground slab whose line-of-sight separation from the stars averages ~0.7 pc. The second layer is also optically thin in most locations and may lie at less than half the separation of the first layer, perhaps with some material among or behind the stars. The association of nebulosities peripheral to the main condensation around the brightest stars is not clear. Models with standard grain properties cannot account for the faintness of the scattered UV light relative to the optical. Some combination of significant changes in grain model albedo and phase function asymmetry values is required. Our best-performing model has a UV albedo of 0.22 ± 0.07 and a scattering asymmetry of 0.74 ± 0.06. Hypothetical optically thick dust clumps missed by interstellar sight line measurements have little effect on the nebular colors but might shift the interpretation of our derived scattering properties from individual grains to the bulk medium.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".