Comparing petrographic and paleo-hydraulic methods for estimating of paleo-drainage basin size: an example from the Cretaceous and Tertiary Bonnet Plume Basin (NTS 106E) Yukon
Bibliographic record
Abstract
Summary One of the key problems in understanding the evolution of terrestrial clastic depositional basins is estimating the size of the catchment area. This can be done using a variety of field observations of sedimentary structures, including cross-bed thickness and direction, channel and storey thickness and channel dimensions. These are used to predict flow velocity, mean annual and bank-full discharge, sinuosity, meander wavelength and ultimately drainage basin size. The mathematical products of these observations can be directly tested using petrographic analysis of sand and gravel grade clasts that have survived erosion and transport from the source area. This is especially practical in areas where the basin is surrounded by a broad range of rock types. In this study, predominantly fluvial strata from the upper and lower members of the Bonnet Plume Formation in the Bonnet Plume Basin (NTS 106E) (Fig 1-Left) were examined physically and petrographically to determine if these approaches produced comparable results. The basin is a structural and physiographic depression at the intersection of the Richardson Mountains and the Mackenzie Mountain front. It was formed in a trans-tensional setting at the same time as mountain building in western Canada. The basin fill has been divided into a lower and upper member of Cretaceous and Tertiary age (Fig 1-Right) and contains significant coal reserves (Long 1986), as well as having limited oil and gas potential (Lowey 2009).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 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".