Planetary wave-tide nonlinear interactions increase the variety of MLT waves in summer 2019
Bibliographic record
Abstract
Mesospheric winds collected by multiple meteor radars at mid-latitudes in the northern hemispheric are combined to investigate wave activities in June—October 2019. Dual-station approaches are developed and implemented to diagnose zonal wavenumber $m$ of spectral peaks. In September—October, diagnosed are quasi‐10‐ and 6‐day planetary waves (Q10DW and Q6DW, $m=$1), solar semi-diurnal tides with $m=$1, 2, 3 (SW1, SW2, and SW3), lunar semi-diurnal tide, and the upper and lower sidebands (USB and LSB, $m=$ 1 and 3) of Q10DW‐SW2 nonlinear interactions. During June— September, diagnosed are Rossby-gravity modes ($m=$3 and 4 at periods $T=$ 2.1d and 1.7d), and their USBs and LSBs generated from interactions with diurnal, semi-diurnal, ter-diurnal, and quatra-diurnal migrating tides. These results demonstrate that the planetary wave-tide nonlinear interactions significantly increase the variety of waves in the mesosphere and lower thermosphere region (MLT).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".