Constraining the Dust Opacity Law in Three Small and Isolated Molecular Clouds
Bibliographic record
Abstract
Abstract Density profiles of isolated cores derived from thermal dust continuum emission rely on models of dust properties, such as mass opacity, that are poorly constrained. With complementary measures from near-infrared extinction maps, we can assess the reliability of commonly used dust models. In this work, we compare Herschel-derived maps of the optical depth with equivalent maps derived from CFHT WIRCAM near-infrared observations for three isolated cores: CB 68, L 429, and L 1552. We assess the dust opacities provided from four models: OH1a, OH5a, Orm1, and Orm4. Although the consistency of the models differs between the three sources, the results suggest that the optical properties of dust in the envelopes of the cores are best described by either silicate and bare graphite grains (e.g., Orm1) or carbonaceous grains with some coagulation and either thin or no ice mantles (e.g., OH5a). None of the models, however, individually produced the most consistent optical depth maps for every source. The results suggest that either the dust in the cores is not well-described by any one dust property model, the application of the dust models cannot be extended beyond the very center of the cores, or more complex SED fitting functions are necessary.
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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 | 0.001 | 0.001 |
| 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".