Stochastic surface-based modeling of turbidite lobes
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Flow event deposits in turbidite lobes are modeled with stochastic surface-based simulation. This method honors the geometries and compensational stacking of flow event deposits. Flow event deposit geometries are based on a flexible lobe parameterization. Compensational stacking is the tendency of flow event deposits to fill topographic lows and to smoothing of topographic relief. The surface-based model may be conditioned to well data. Models of reservoir properties such as porosity and permeability are constrained by the resulting geometric models. This approach is applied in a geostatistical workflow to better integrate available geologic information. The resulting models may improve the accuracy of model reservoir response and account for the uncertainty in the heterogeneity of turbidite lobes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it