Loop - Enabling 3D stochastic geological modelling
Bibliographic record
Abstract
SummaryLoop is a new open source 3D geological and geophysical modelling platform in full development.The new platform consists of 4 main work packages: Knowledge Management: use of AI techniques for knowledge extraction from literature, maps and reports using geological ontology. Geological rules will be encoded to ensure proper knowledge extraction.Geological Event Management: Loop is a time-aware geological modelling platform and the event manager is capturing topological and time relationship between geological objects and structural eventsForward and inverse structural modelling: we will encode structural geological rules in a time-aware context to account for folds (including overprinting), faults, shear zones, unconformities and intrusions. The modelling is based on probabilistic modelling and allows for the definition of an objective function for geology and quantification of uncertainty via posterior probabilities.Uncertainty characterisation and modelling: using stochastic simulations or the result of Bayesian modelling, Loop allows for characterisation and quantification of 3D uncertainty.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".