Emerging Perspectives on Mercury's Internal Structure from MESSENGER Flyby Observations and Geophysical Modeling
Bibliographic record
Abstract
FLYBY OBSERVATIONS AND GEOPHYSICAL MODELING. Maria T. Zuber, David E. Smith, Roger J. Phillips, Sean C. Solomon, Gregory A. Neumann, Frank G. Lemoine, Stanton J. Peale, Jean-Luc Margot, Steven A. Hauck, II, James W. Head, Catherine L. Johnson, Michael E. Purucker, Jurgen Oberst10, Grant T. Farmer, Jiangning Lu, Youshun Sun, M. Nafi Toksoz, Olivier S. Barnouin, Mark E. Perry, Dipak K. Srinivasan, Mark H. Torrence, Massachusetts Institute of Technology, Cambridge, MA 02129 (zuber@mit.edu); Southwest Research Institute, Boulder, CO 80302; Carnegie Institution of Washington, Washington, DC 20015; NASA Goddard Space Flight Center, Greenbelt, MD 20771; University of California, Santa Barbara, CA 93106; University of California, Los Angeles, CA 90095; Case Western Reserve University, Cleveland, OH 44106; Brown University, Providence, RI 02912; University of British Columbia, Vancouver, BC, Canada V6T 1Z4; DLR, Berlin, Germany; Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723; SGT, Inc., 7701 Greenbelt Rd., Greenbelt, MD 20770.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".