Informing Lunar and Martian Science Operations Scenarios Through Underwater Analog Mission Activities at Pavilion Lake, Canada
Bibliographic record
Abstract
UNDERWATER ANALOG MISSION ACTIVITIES AT PAVILION LAKE, CANADA. D. S. S. Lim 1,2 , M. Gernhardt 3 , R. Shepard 4 , A. L. Brady 5 , M. M. Marinova 6 , M. Wilhelm 7 , A. Forrest 8 , Z. Cardman 9 , A. Abercromby 3 , M. Deans 1 , D. Lees 1 , R. Arnold 3 , B. Cowie 10 , G. F. Slater 5 , B. Laval 8 , D. Reid 8 and C. P. McKay 1 . 1 NASA Ames Research Center, M-S 245-3, Moffett Field, CA 94025, Darlene.lim@nasa.gov, 2 SETI Institute, 515N Whisman Road, Mountain View, CA, 3 NASA Johnson Space Center, 2101 NASA Parkway Houston, Texas, USA 77058, 4 Geology Department,University of California, One Shields Avenue, Davis, CA USA, 5 School of Geology and Geography, McMaster University, Hamilton, Ontario, Canada, 6 Planetary Science, California Institute of Technology, MC 150-12, Pasadena, CA USA, 7Cornell University, 8 Department of Civil Engineering, University of British Columbia, Vancouver, B.C., Canada, 9 University of North Carolina at Chapel Hill, Department of Marine Sciences, 340 Chapman Hall, CB 3300, Chapel Hill, NC 27599-3300, 10 Applied Geochemistry Group, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".