Preliminary results of shallow subsurface geological mapping, Sabine Peninsula, western Arctic Islands
Bibliographic record
Abstract
The study of the Sabine Peninsula, western Arctic Islands, was undertaken as part of the Government of Canada's Geo-mapping for Energy and Minerals (GEM) program. Given the cost of data acquisition in frontier areas, vintage data sets still possess a strong value. This study utilizes modern geoscientific processing and interpretation methods applied to a suite of data collected during the initial round of exploration that took place between the late 1960s and early 1980s. The focus of this project is to map the subsurface of Sabine Peninsula and provide a more detailed seismic stratigraphy to ultimately develop play concepts that were not identified during the initial round of exploration. Following the reprocessing of the seismic data sets, six time-structure maps of the Triassic through Cretaceous succession of the Sverdrup Basin (<3 s) display changes in the morphology of the horizons throughout the Mesozoic. Several features are preserved throughout the Mesozoic section, for instance, the presence of a linear flexure inherited from the deeper section (possibly Permian) indicates the loca-tion of a possible paleoshelf edge. Additionally, the presence of a depression, and the gradual infill of that depression provide clues as to what type of seismic successions can be expected in the deeper section and the adjacent offshore.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.008 | 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".