International observational campaign of the 2014 eclipse of EE Cephei
Bibliographic record
Abstract
Context. EE Cep is one of few eclipsing binary systems with a dark, dusty disc around an invisible object similar to ε Aur. The system is characterised by grey and asymmetric eclipses every 5.6 yr that have significant variations in their photometric depth, ranging from ∼0.m5 to ∼2.m0. Aims. The main aim of the observational campaign of the EE Cep eclipse in 2014 was to test the model of disc precession. We expected that this eclipse would be one of the deepest with a depth of ∼2.m0. Methods. We collected multicoloured observations from almost 30 instruments located in Europe and North America. These photometric data cover 243 nights during and around the eclipse. We also analyzed low- and high-resolution spectra from several instruments. Results. The eclipse was shallow with a depth of 0.m71 in the V band. The multicoloured photometry illustrates small colour changes during the eclipse with a total amplitude of order ∼+0.m15 in the B − I colour index. We updated the linear ephemeris for this system by including new times of minima, measured from the three most recent eclipses at epochs E = 9, 10, and 11. We acquired new spectroscopic observations, covering orbital phases around the eclipse, which were not observed in the past and increased the data sample, filling some gaps and giving better insight into the evolution of the Hα and Na I spectral line profiles during the primary eclipse. Conclusions. The eclipse of EE Cep in 2014 was shallower than expected, measuring 0.m71 instead of ∼2.m0. This means that our model of disc precession needs revision.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".