Field Demonstration of an Instrument Performing Automatic Classification of Geologic Surfaces
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This work presents a method with which to automate simple aspects of geologic image analysis during space exploration. Automated image analysis on board the spacecraft can make operations more efficient by generating compressed maps of long traverses for summary downlink. It can also enable immediate automatic responses to science targets of opportunity, improving the quality of targeted measurements collected with each command cycle. In addition, automated analyses on Earth can process large image catalogs, such as the growing database of Mars surface images, permitting more timely and quantitative summaries that inform tactical mission operations. We present TextureCam, a new instrument that incorporates real-time image analysis to produce texture-sensitive classifications of geologic surfaces in mesoscale scenes. A series of tests at the Cima Volcanic Field in the Mojave Desert, California, demonstrated mesoscale surficial mapping at two distinct sites of geologic interest.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it