Edge detection applied to Cassini images reveals no measurable displacement of Ontario Lacus' margin between 2005 and 2010
Bibliographic record
Abstract
Ontario Lacus is thus far the largest flat‐floored topographic depression of Titan's southern hemisphere interpreted as a permanent or ephemeral lake. From 2005 to 2010, it was imaged several times and at various wavelengths by ISS, VIMS and RADAR instruments onboard Cassini's spacecraft. We analyze the position and uncertainty of Ontario Lacus' margin in all these images using an edge detection method based on image derivation. We find that, given the range of uncertainties in contour locations derived from images, no measurable displacement of Ontario Lacus' margin can be detected between 2005 and 2010 at the actual image spatial resolutions. The discrepancy between this result and previous ones is attributable to differences in (1) the basics behind the methods used, (2) the actual spatial resolutions and contrasts of the available images due to differential atmospheric scattering effects at different wavelengths, and (3) the geomorphological interpretation of contours derived from images acquired at different wavelengths. This lack of measurable displacement in the images suggests that the imaged contour corresponds either (1) to the border of a surface liquid body, provided that potential changes in its extent over five terrestrial years were not sufficiently large to be measured, or (2) to the stationary topographic border between Ontario Lacus' depression and the surrounding alluvial plain. Potential displacements of Ontario Lacus' margin between 2005 and 2010 are thus below the actual resolution of currently available images or have to be sought for within the extent of the topographic depression rather than along its borders.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".