The FORS1 catalogue of stellar magnetic field measurements?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Context. The FORS1 instrument on the ESO Very Large Telescope was used to obtain low-resolution circular polarised spectra of nearly a thousand different stars, with the aim of measuring their mean longitudinal magnetic fields. Magnetic fields were measured by different authors, and using different methods and software tools. Aims. A catalogue of FORS1 magnetic measurements would provide a valuable resource with which to better understand the strengths and limitations of this instrument and of similar low-dispersion, Cassegrain spectropolarimeters. However, FORS1 data reduction has been carried out by a number of different groups using a variety of reduction and analysis techniques. Our understanding of the instrument and our data reduction techniques have both improved over time. A full re-analysis of FORS1 archive data using a consistent and fully documented algorithm would optimise the accuracy and usefulness of a catalogue of field measurements. Methods. Based on the ESO FORS pipeline, we have developed a semi-automatic procedure for magnetic field determinations, which includes self-consistent checks for field detection reliability. We have applied our procedure to the full content of circular spectropolarimetric measurements of the FORS1 archive. Results. We have produced a catalogue of spectro-polarimetric observations and magnetic field measurements for ∼ 1400 observa-tions of ∼ 850 different objects. The spectral type of each object has been accurately classified. We have also been able to test different methods for data reduction is a systematic way. The resulting catalogue has been used to produce an estimator for an upper limit to
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it