Arctic Ocean seafloor surface geology based on interpretation of acoustic facies inferred from sub-bottom profiles acquired with icebreaker Oden
Bibliographic record
Abstract
The Arctic Ocean, its connection to the Atlantic Ocean, and the surrounding land and cryosphereplay critical roles in regulating the global climate system. This region has undergone an exponential increase in research during the last few decades, leading to the release of four versionsof the IBCAO bathymetric grid since then. Nevertheless, the compilation of the seafloor geology and uppermost sediment layers only began in 2015 under the “IBCAO Geology” project ledby the Geological Survey of Canada, starting with the creation of a surficial geology map of theAmerasia Basin of the Arctic Ocean. As an expansion of this effort, a surficial geology map ofthe Eurasia Basin and its connection to the Atlantic was produced in this study. The compilationis based on the interpretation of acoustic facies inferred from sub-bottom profiles acquired withicebreakers, using both systematically collected data and transit data that often go unnoticed.Additional interpretations were made with the support of the IBCAO bathymetric grid in orderto explain the processes that shape and shaped the seafloor and sub-bottom. Integrating theIBCAO Geology and IBCAO bathymetric grid thus provides a comprehensive understanding ofthe Arctic Ocean seafloor and its uppermost sediment layers, serving as a foundation for futureresearch and survey planning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".