Bibliographic record
Abstract
A new technique for calibrating optical long-baseline interferometric observations is developed where both the calibration corrections and the source characteristics are obtained from the observations of a program star. This calibration technique can only be applied to certain classes of objects, such as emission line sources or binary systems, where the parameters describing the characteristics of the source have different functional dependence than the calibration parameters. To demonstrate its effectiveness, the technique is applied to observations of four different Be stars obtained with the Navy Prototype Optical Interferometer. The interferometric observations utilize measurements obtained simultaneously in many spectral channels covering a wide spectral range, where only two channels contain a strong signal due to the circumstellar envelope in the Halpha emission line. The calibrated observations in Halpha allow modeling of the circumstellar envelopes of all four stars with circularly symmetric and elliptical Gaussian models. The best-fit model parameters are then combined with similar results for other Be stars, already published in the literature, to study the relationship between the Ha emission and the physical extent of the Halpha-emitting circumstellar region. For the first time, a clear dependence of the net Halpha emission on the extent of the circumstellar region is demonstrated. These results are consistent with an optically thick line emission that is directly proportional to the effective area of the emitting disk. Within the small sample of stars considered in this analysis, no clear dependence on the spectral type or stellar rotation is established, although the results do suggest that hotter stars might have more extended circumstellar regions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".