A quasi-time-dependent radiative transfer model of OH 104.9+2.4
Bibliographic record
Abstract
We investigate the pulsation-phase dependent properties of the circumstellar dust shell (CDS) of the OH/IR star OH 104.9+2.4 based on radiative transfer modeling (RTM) using the code DUSTY. Our previous study concerning simultaneous modeling of the spectral energy distribution (SED) and near-infrared (NIR) visibilities (Riechers et al. 2004) has now been extended by means of a more detailed analysis of the pulsation-phase dependence of the model parameters of OH 104.9+2.4. In order to investigate the temporal variation in the spatial structure of the CDS, additional NIR speckle interferometric observations in the K' band were carried out with the 6 m telescope of the Special Astrophysical Observatory (SAO). At a wavelength of m the diffraction-limited resolution of 74 mas was attained. Several key parameters of our previous best-fitting model had to be adjusted in order to be consistent with the newly extended amount of observational data. It was found that a simple rescaling of the bolometric flux Fbol is not sufficient to take the variability of the source into account, as the change in optical depth τ over a full pulsation cycle is rather high. On the other hand, the impact of a change in effective temperature Teff on SED and visibility is rather small. However, observations, as well as models for other AGB stars, show the necessity of including a variation of Teff with pulsation phase in the radiative transfer models. Therefore, our new best-fitting model accounts for these changes.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".