BOLIDE DYNAMICS AND LUMINOSITY MODELING: COMPARISONS BETWEEN UNIFORM BULK DENSITY AND POROUS METEOROID MODELS
Bibliographic record
Abstract
We compare predictions of bolide behavior using basic meteoroid models, first assuming a uniform bulk density throughout the body and secondly assuming a uniform chondritic composition throughout, but with varying amounts of porosity (assumed to be filled with either water-ice or open space).The second model is based one the uniformity of spectral observations over many years from shower meteors from the extremes of the Geminids to the dustball-like Draconids.The first model utilized is due to ReVelle (1979ReVelle ( , 1993) ) and the second is based upon the porous meteoroid model of ReVelle (1983ReVelle ( , 1993)).The standard, uniform bulk density model assumes that the drag and heat transfer area are equivalent in the positive, shape change factor limit.For porous meteoroids however, the heat transfer area can exceed the drag area by increasingly larger amounts as the body's porosity increases.ReVelle (1983) used this approach to show that the bulk density and ablation parameter compositional group identifications of Ceplecha and McCrosky (1976) were essentially correct.When these factors are introduced into the relevant model equations, a set of nearly selfconsistent predictive relations are developed which readily allows comparisons to be made of the end-height variations and of the normalized luminous output of the two basic meteoroid models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".