A new method for measuring the meteor mass index: application to the 2018 Draconid meteor shower outburst
Bibliographic record
Abstract
Context. Several authors predicted an outburst of the Draconid meteor shower in 2018, but with an uncertain level of activity. Aims. Optical meteor observations were used to derive the population and mass indices, flux, and radiant positions of Draconid meteors. Methods. We performed 90 min of multi-station observations after the predicted peak of activity using highly sensitive Electron Multiplying Charge Coupled Device cameras. The data calibration is discussed in detail. A novel maximum likelihood estimation method was developed to compute the population and mass index with robust error estimation. We applied the method to observed Draconids and used the values to derive the flux. Meteor trajectories were computed and compared to predicted radiant positions from meteoroid ejection models. Results. We find a mass index of 1.74 ± 0.18 in the 30 min bin after the predicted peak, and 2.32 ± 0.27 in the subsequent 60 min. The location and the dispersion of the radiant are a good match to modeled values, but there is an offset of 0.4° in solar longitude.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".