Using Open Science To Determine Physical Properties of Near Earth Asteroids
Bibliographic record
Abstract
Title: Using Open Science To Determine Physical Properties of Near Earth Asteroids Presenter: Arushi Nath (Founder MonitorMyPlanet.com, Canada) This was a poster presented at the 5th Shaw-IAU Workshop on Astronomy for Education, organised by the IAU Office of Astronomy for Education (OAE, http//astro4edu.org). The pace of discovery of near-earth asteroids outpaces current abilities to analyze them. Knowledge of an asteroid's physical properties is essential to deflect them. I have developed open-source algorithms for classrooms that combine images from robotic telescopes, open-data, and math to determine asteroids' size, rotation, and strength. I took observations of the Didymos binary asteroid, and my algorithm determined it to be 820m wide, with a 2.26-hour rotation period and rubble-pile strength. I measured a 35-minute decrease in the mutual orbital period after impact by the 2022 NASA DART Mission. External sources validated the findings. Every citizen scientist is now a planetary defender. The project won the 2023 Youth Astronomy Award of the Royal Astronomical Society of Canada. About the 5th Shaw-IAU Workshop on Astronomy for Education:This year’s Shaw-IAU Workshop on Astronomy for Education focuses on two themes: one special practical astronomy education topic and one scientific topic. The special topic is astronomy education outside the classroom, looking at how astronomy can be taught in a diverse range of environments such as science centers, planetaria and youth clubs. The scientific topic is planetary atmospheres, both in the solar system and exoplanets as well as our own Earth. The workshop was organised by the IAU Office of Astronomy for Education (http://astro4edu.org). More details can be found on: https://astro4edu.org/shaw-iau/5th-shaw-iau-workshop/schedule/ Keep up to date with future Shaw-IAU Workshops and other opportunities at the IAU Office of Astronomy for Education by joining our mailing list https://astro4edu.org/mailing-list/ Follow the IAU OAE on X and Facebook under @astro4edu
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".