Dynamical resonant structures in meteoroid stream orbits
Bibliographic record
Abstract
Herein we use the Canadian Meteor Orbit Radar (CMOR) data set to search for evidence of a resonant swarm in the Taurid meteoroid stream at the 7:2 Jovian resonance. We use a numerical method to estimate the reduction in radar orbit measurement uncertainty required to detect this feature in a data set. This is highly dependent on the proportion of observed particles that are members of the resonant swarm. However, we find that a meteor radar with uncertainties a factor of 10 lower than those of the current CMOR will be sufficient for detection to be possible, if the meteor shower consists of more than 5 per cent resonant particles (considered likely given the results of visual meteor studies). Such an improvement will require accurate removal of deceleration errors from pre-atmospheric meteor velocities, and improvement to the robustness of echo inflection point identification algorithms and interferometric measurements.
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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) | 0.001 | 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".