THE NEAR EARTH OBJECT SURVEILLANCE SATELLITE (NEOSSat) MISSION WILL CONDUCT AN EFFICIENT SPACE-BASED ASTEROID SURVEY AT LOW SOLAR ELONGATIONS. Hildebrand
Bibliographic record
Abstract
AN EFFICIENT SPACE-BASED ASTEROID SURVEY AT LOW SOLAR ELONGATIONS. Hildebrand A.R., Tedesco E.F., Carroll K.A., Cardinal R.D., Matthews J.M., Gladman, B., Kaiser, N.R., Brown P.G., Wiegert, P., Larson S.M., Worden, S.P., Wallace, B.J., Chodas P.W., Granvik, M., Gural P. Department of Geoscience, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada T2N 1N4 (ahildebr@ucalgary.ca); Planetary Science Institute, 1700 E. Fort Lowell, Suite 106, Tucson, AZ, USA 857192395; 3 Gondola Crescent, Brampton, Ontario L6S 1W5; Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC, Canada V6T 1Z1; Department of Physics and Astronomy, The University of Western Ontario, London, ON, Canada N6A 3K7; Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ, USA 85721; NASA Ames Research Center, Moffett Field, CA, USA 94035; Defence Research & Development Canada, 3701 Carling Ave., Ottawa, ON, Canada K1A 0Z4; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA 91109; Observatory, Kopernikuksentie 1, P.O. Box 14, FIN-00014, University of Helsinki, Finland; Science Applications International Corporation, 4501 Daly Drive, Suite 500, Chantilly, VA, USA 20151.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".