A Method for Internal Calibration of Optical Interferometer Data and Application to the Circumstellar Envelope of Cassiopeiae
Bibliographic record
Abstract
We present a technique for calibrating optical long-baseline interferometric observations in which both the calibration corrections and the source characteristics are obtained from the observations of a program star. This calibration can only be applied to certain classes of objects, such as emission-line sources or binary systems, in which the parameters describing the characteristics of the source are orthogonal to the calibration parameters. The technique is applied to observations of γ Cassiopeiae, obtained on four different nights with the Navy Prototype Optical Interferometer, and utilizes measurements obtained simultaneously in many spectral channels covering a wide spectral range, of which only two channels contain a strong signal due to the circumstellar envelope in the Hα emission line. The calibrated observations in Hα show a clearly resolved circumstellar structure. The best-fit elliptical Gaussian model fitted to our observations has ensemble average parameters of 3.67 ± 0.09 mas for the angular size of the major axis, 0.79 ± 0.03 for the axial ratio, and 32° ± 5° for the position angle, all in good agreement with values reported by previous investigations.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".