An example of alternative correlation techniques in a low-accommodation setting, nonmarine hydrocarbon system: The (Lower Cretaceous) Mannville Basal Quartz succession of southern Alberta
Bibliographic record
Abstract
Abstract Chemostratigraphy and heavy-mineral techniques have been applied to the Lower Cretaceous Basal Quartz in the Western Canada sedimentary basin. The aim of the study is to demonstrate that these two techniques can be used to help understand the complex stratigraphy of reservoirs deposited in low-accommodation fluvial settings. The Basal Quartz is an ideal unit to demonstrate their applicability in stratigraphic studies of hydrocarbon reservoirs because extensive mapping and petrographic studies have enabled the establishment of a rigorous stratigraphic framework despite its complexity resulting from deposition in a low-accommodation fluvial setting. The three component units analyzed in the Basal Quartz (Horsefly unit, Bantry–Alderson–Taber [BAT] unit, and Ellerslie unit) each have unique geochemical and heavy-mineral characteristics. Chemostratigraphic analysis shows that silty claystones from the Horsefly, BAT, and Ellerslie units have distinctly different geochemistry from one another, with the variations being caused by changes in clay mineralogy and other components, such as feldspar, apatite, and zircon. The geochemistry also suggests periodic volcanogenic input influenced the silty claystones of the Basal Quartz. Heavy-mineral analysis shows that sandstones from the three units can be distinguished on the basis of ratio parameters, such as apatite/tourmaline, rutile/zircon, and zircon/tourmaline, which are controlled by differences in provenance and intensity of weathering during transport.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".