Smart Modelling of Geologic Stratigraphy Concepts using Sketches
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Several applications of Earth Science require geologically valid interpretation and visualization of complex physical structures in data-poor subsurface environments. Hand-drawn sketches and illustrations are standard practices used by domain experts for conceptualizing their observations and interpretations. These conceptual geo-sketches provide rich visual references for exploring uncertainties and helping users formulate ideas, suggest possible solutions, and make critical decisions affecting the various stages in geoscience studies and modelling workflows. In this paper, we present a sketch-based interfaces and modelling (SBIM) approach for the rapid conceptual construction of stratigraphic surfaces, which are common to most geologic modelling scales, studies, and workflows. Our SBIM approach mirrors the way domain users produce geo-sketches and uses them to construct 3D geologic models, enforcing algorithmic rules to ensure geologically-sound stratigraphic relationships are generated, and supporting different scales of geology being observed and interpreted. Results are presented for two case studies demonstrating the flexibility and broad applicability of our rule-based SBIM approach for conceptual stratigraphy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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