Meteor luminous efficiencies from simultaneous multi-frequency radar and high-resolution optical observations
Bibliographic record
Abstract
We examine the effects of assumptions in the calculation of electron line density of radar meteors on the value of luminous efficiency calculated using simultaneous radar and optical observations. We combine high-resolution optical measurements from the Canadian Automated Meteor Observatory (CAMO) with multi-frequency radar echoes from the Canadian Meteor Orbit Radar (CMOR). Previous work relating β and τ has been limited to single-frequency radar observations, which requires additional modelling assumptions such as the initial trail radius (Weryk and Brown, 2013). In this work, we require model fits to all three frequencies at which CMOR operates, which provides better constraints which reduce the need for these assumptions, at the cost of significantly shrinking the pool of suitable data. Between 2017–2022, 299 candidates for three-frequency CMOR simultaneously observed by CAMO were identified, of which 1% were suitable for fitting. Although the fittable data set was too small to determine statistical trends, all events showed lower luminous efficiencies than those that would be found through single-frequency modelling. This emphasizes the need for better models of scattering from meteor trails in these studies.
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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 | 0.000 | 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 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".