Combining Rosetta’s GIADA and MIDAS data: morphological versus dynamical properties of dust at 67P/Churyumov–Gerasimenko
Bibliographic record
Abstract
ABSTRACT We related morphological (size/shape) and dynamical properties of the dust ejected from the 67P/Churyumov–Gerasimenko comet by combining data from two instruments onboard the ESA's Rosetta mission, i.e. the MIDAS atomic force microscope and the GIADA dust detector. The two instruments detected dust of different size (10−6–10−5 and 10−4–10−3 m, respectively). MIDAS detected dust in four periods, three during the inbound orbit arc (2014 September–November; 2014 December– 2015 February; 2015 February–March) and one corresponding to a post-perihelion outburst (2016 February 19). For these periods, we analysed the dust particles’ spatial distribution on the MIDAS targets to obtain the number of parent particles hitting the instrument by means of an empirical procedure and to measure the corresponding dust flux. For the same periods, we retrieved the dust flux measured by GIADA. The ratio between the two dust fluxes is constant. By coupling this result with activity models, we inferred that the particles detected by MIDAS are fragments of hundreds-micron- to mm-sized particles detected by GIADA. In addition, the similar dust flux ratios between nominal activity and outburst indicates that the outburst did not include micro- and nano-sized dust, differently from other outbursts previously observed. Dust and surface properties were related by applying a traceback algorithm to GIADA data to retrieve the source regions of dust ejected in different periods. We did not detect variations of morphological properties between dust ejected from more and less processed terrains, concluding that compact dust particles (detected by MIDAS) have the same properties across the comet surface.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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 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".