Photometric and ionization masses of meteors with simultaneous EISCAT UHF radar and intensified video observations
Bibliographic record
Abstract
There are significant uncertainties in the calculation of photometric and ionization masses of meteors, particularly those derived from meteor head echoes observed by high power, large aperture radars. Simultaneous observations of meteors with the EISCAT UHF tristatic system and narrow field two‐station intensified video were conducted in October 2007; 11 hours of data produced four useful meteors observed on all three radar receivers and both cameras. The positions and speeds calculated on the two systems generally agree to within the observational uncertainty. The photometric and ionization masses for each meteor were calculated using several values of luminous efficiency and ionization probability from literature, and all of these masses were found to agree to within the estimated error in the methods. More observations are required to select among the various values of ionization coefficient and luminous efficiency.
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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 | 0.001 |
| 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".