Bibliographic record
Abstract
Abstract The mechanical properties of clay minerals are important in many diverse scientific disciplines, including soil mechanics, civil engineering, materials science, and petroleum exploration. Rock physics provides a link between the elastic properties of rocks and their constitutive properties such as mineralogic composition, porosity, and pore‐fluid content. To accurately characterize shales, rock physics models must account for the anisotropic properties of clay minerals. Due to more compliant regions between clay particles, the elastic stiffness of clay in shales is significantly less than that of its constituent clay minerals. In this paper, the clay in shales is modeled as anisotropic clay platelets surrounded by a softer interparticle region consisting of clay‐bound water and interparticle contacts. Inverting for the elastic properties of this interparticle region indicates that its effective bulk modulus is like that of water. However, it has a nonzero effective shear modulus that is smaller by an order of magnitude, consistent with the expected shear modulus of clay‐bound water. Owing to its simplicity and robustness, it is anticipated that this model of shales, based on the properties of clay minerals and the interparticle medium, will find use in many rock physics applications, including seismic imaging, seismic inversion, and geomechanics.
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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 | 0.000 |
| 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) | 0.001 | 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".