North Alaska petroleum system analysis: The regional map compilation
Bibliographic record
Abstract
The U.S. Geological Survey initiated an effort to model north Alaskan petroleum systems. The geographic and geologic basis for modeling systems is provided by a set of regional digital maps that allow evaluation of the widest possible extent of each system. Accordingly, we laid out a rectangular map grid 1300 km (800 miles) east-west and 600 km (375 miles) north-south. The resulting map area extends from the Yukon Territory of Canada on the east to the Russian-U.S. Chukchi Sea on the west and from the Brooks Range on the south to the Canada basin-Chukchi borderland on the north. Within this map region, we combined disparate types of publicly available data to produce structure contour maps. Data types range from seismic-based mapping as in the National Petroleum Reserve to well penetrations in areas of little or no seismic data where extrapolation was required. With these types of data, we produced structure contour maps on three horizons: top of pre-Mississippian (basement), top of Triassic (Ellesmerian sequence), and top of Neocomian (Beaufortian sequence). These horizons, when combined with present-day topography and bathymetry, provide the bounding structural/stratigraphic surfaces of the north Alaskan petroleum province that mark major defining moments of the region's geologic history and allow regional portrayal of preserved sediment accumulations.
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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 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 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".