Quantified energy dissipation rates in the terrestrial bow shock: 1. Analysis techniques and methodology
Bibliographic record
Abstract
Abstract We present a detailed outline and discussion of the analysis techniques used to compare the relevance of different energy dissipation mechanisms at collisionless shock waves. We show that the low‐frequency, quasi‐static fields contribute less to ohmic energy dissipation, (−j·E), than their high‐frequency counterparts. In fact, we found that high‐frequency, large‐amplitude (>100 mV/m and/or >1 nT) waves are ubiquitous in the transition region of collisionless shocks. We quantitatively show that their fields, through wave‐particle interactions, cause enough energy dissipation to regulate the global structure of collisionless shocks. The purpose of this paper, part one of two, is to outline and describe in detail the background, analysis techniques, and theoretical motivation for our new results presented in the companion paper. The companion paper presents the results of our quantitative energy dissipation rate estimates and discusses the implications. Together, the two manuscripts present the first study quantifying the contribution that high‐frequency waves provide, through wave‐particle interactions, to the total energy dissipation budget of collisionless shock waves.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".