SeafloorMapper: A GUI-Based Application for Manual and Automatic Extraction of Seafloor Photons from ICESat-2 ATL03 Data
Bibliographic record
Abstract
SeafloorMapper is a GUI-based application designed for identification of seafloor photons with ICESat-2 ATL03 data. The software integrates two mapping modes, manual and automatic, and three workflows for generating datasets in different formats according to users’ needs. Workflow tools include data pre-processing, manual and automated seafloor photon identification, manual post-processing, and creation of training data for the AI model used for automated seafloor photon identification. We demonstrate the software with two case studies, one conducted in Cambridge Bay, Canada, where seafloor depths obtained from ATL03 data using SeafloorMapper were compared against survey data from the Canadian Hydrographic Service, and another conducted at Sanikiluaq, Canada, where seafloor depths derived from ICESat-2, in the absence of other bathymetric information, were used to produce satellite-derived bathymetry for the area. SeafloorMapper is a useful and robust tool to extract bathymetric information from ATL03 data.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.009 |
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".