Listening to shower meteors with infrasound
Bibliographic record
Abstract
Observations of the Leonid and Perseid meteor showers over the last few years in Europe using multiple camera systems, including the European Fireball Camera Network, have shown several bright meteors (abs. magnitudes −8 to −16) passing nearby to the IMS infrasound array in Freyung, Germany (I26DE). Subsequent checks of I26DE data show that these meteors were also detected infrasonically. This combination of optical location of the meteor in flight and microbarometer array beamforming has provided an excellent opportunity to delimit the altitudes at which these infrasound signals are being generated. UKMO temperature and wind data from the UARS satellite has been combined with MSIS and HWM models to reconstruct the acoustic velocity conditions present during observations. Using the reconstructed conditions, geometric ray tracing indicates that the source altitudes lie between approximately 80 to 105 kilometers; array back-azimuths appear to confirm this conclusion. This is extraordinary since meteoroids of this size, at these altitudes in the atmosphere, are in the transitional region from free-molecular flow to continuum flow. With these observations there is now confirmed infrasound from three separate meteor showers; the Leonids, Geminids and Perseids, meaning that meteor shower infrasound is much more common than previously thought.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
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 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".