A pore-size scale model for the dielectric properties of water-saturated clean rocks and soils
Bibliographic record
Abstract
Abstract The dielectric properties of water-saturated rock and soils are strongly dependent on the amount and nature of their porosity; interpretation of these geophysical data requires petrophysical models that incorporate both of these elements. The differential effective medium approximation (DEMA) is used to develop a dielectric permittivity model for clean (i.e., clay free) media that divides the pore spaces into elements corresponding to three categories of relative size scale: microscopic porosity (e.g., intergranular cracks), mesoscopic porosity (e.g., main pore volumes), and macroscopic porosity (e.g., vugs and fractures). The hierarchical size-scale structure imposed by the DEMA iterative embedding process is used to assign each pore space category its role in model construction. Use of this model demonstrates that the relationship between dielectric permittivity and porosity is significantly affected by the size scales of pores present in the rock models. A region of realizable permittivity-porosity values is obtained by varying the pore structure in the scaled-porosity model. The bounds of this region correspond to end-member porosity models. Analysis of experimental permittivity data for water-saturated sandstones and carbonates that cover a substantial range of porosity values found that the scaled-porosity models account for a significant part of the variability in experimental data.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".